投稿時間:2021-08-14 01:21:06 RSSフィード2021-08-14 01:00 分まとめ(29件)

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AWS	lambdaタグが付けられた新着投稿 - Qiita	AWS Toolkit とsam を使ってLambdaを実行（ローカル実行、API Gateway実行）	https://qiita.com/ssugimoto/items/33a01e8bfbc385a79b52	AWS公式で、IfyoureusingWindowsinHyperVmodeseefilesharingWindowsに入れたVSCodeに拡張機能AWSToolkitをインストールWindowsにPythonSAMCLIのインストールPythonをインストールPythonのインストーラーが見つからない、Pythonを使うことにする。	2021-08-14 00:01:09
python	Pythonタグが付けられた新着投稿 - Qiita	Alembicでバージョンがおかしくなってしまったときの対処法	https://qiita.com/ys_ced/items/2ab256f422305f9af05b	migrationのバージョンwpakmy最初のスクリプトjufipnimxydtnxynjalembicはここまで実行したと思っているipmktzfxyjgmsztewFooテーブルを作るスクリプトmffcnここから実行すればOKなはずhkuseazdckheadAlembicのバージョンを変更するAlembicは、実行したmigrationの最新バージョンがどれか、という情報をalembicversionテーブルに保持しています。	2021-08-14 00:34:40
python	Pythonタグが付けられた新着投稿 - Qiita	PythonでScryfallからMagic: the Gatheringのカードの情報をゲットした話	https://qiita.com/Takeshi_Sue/items/6d15dddff2db4874952c	問題なのは、その特定のカードの裁定はURIとしてリンク先のみ提供されていることです。	2021-08-14 00:06:17
js	JavaScriptタグが付けられた新着投稿 - Qiita	Windows 10 + Node.js + VSCode で React の開発環境を準備する	https://qiita.com/kerobot/items/febe52f8f8f126a763b9	gtnodeversionvgtnpmversionCreateReactAppを利用したプロジェクトの作成と実行Nodejsに含まれるnpxというコマンドを用いて「CreateReactApp」というプログラムを実行することで、React開発のプロジェクトを作成することができます。	2021-08-14 00:41:53
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	discord.pyで音声再生中に新たな入力を受け付けない	https://teratail.com/questions/354178?rss=all	読み上げにはVoiceTextのAPIを使用してwaveファイルを取得し、ffmpegPCMAudioで再生しています。	2021-08-14 00:55:36
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	背景画像が表示されません	https://teratail.com/questions/354177?rss=all	背景画像が表示されません前提・実現したいことRubynbsponnbspRailsでwebアプリを作っています。	2021-08-14 00:54:12
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	swift 起動画面を画像アニメーションにする（ツイッターのようなスプラッシュではなく）	https://teratail.com/questions/354176?rss=all	swift起動画面を画像アニメーションにするツイッターのようなスプラッシュではなく前提・実現したいことここに質問の内容を詳しく書いてください。	2021-08-14 00:52:40
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	minitestのエラーについて	https://teratail.com/questions/354175?rss=all	minitestのエラーについてmoduleDeepFreezabledefdeepfreezearrayorhasharrayorhasheachdoelementelementfreezeendarrayorhashfreezeendendrequirelibdeepfreezableclassTeamextendDeepFreezableCOUNTRIESdeepfreezeJapanUSIndiaend↑このつのコードをlibディレクトリに保存しました。	2021-08-14 00:44:37
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	グラフ横軸の時間目盛りの最小、最大を設定したい	https://teratail.com/questions/354174?rss=all	グラフ横軸の時間目盛りの最小、最大を設定したい前提・実現したいこと機械稼働状況グラフの横軸表示を時スタートで時終了としたい。	2021-08-14 00:39:18
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Selenium 特定のサイトで要素の取得ができない	https://teratail.com/questions/354173?rss=all	実現したいことは、入力ボックス要素の取得→ボックスへの入力です。	2021-08-14 00:24:05
Docker	dockerタグが付けられた新着投稿 - Qiita	GradleでFlywayでMySQLをマイグレーション on Docker	https://qiita.com/kazzool/items/b1ef0220aec621578902	DockerComposeローカルに依存しない環境配布をするため全部コンテナ化MigrateServiceDockerコンテナ内でGradleプロジェクトとして動かすCIする時のことを考慮してDockerイメージを…とか色々考えたけど、あらゆる環境パターンを考慮するとか面倒臭すぎてあきらめ…flywayのdockerイメージもあったけど、csvインポートでInsert文生成とかも考えてGradle経由にこれ結局開発過程でJava書くやんけ…ってDatabaseServiceMySQLの初期セットアップも省けてうれしいやってみるまずはDatabaseServiceMySQLのコンテナを作る必要なファイルを作成する。	2021-08-14 01:00:03
Docker	dockerタグが付けられた新着投稿 - Qiita	Selenium + OpenCV のコンテナ	https://qiita.com/kempe/items/54e32313c9e91d295426	SeleniumOpenCVのコンテナ動機SeleniumとOpenCVが同居したコンテナが必要だったが軽量なものが存在しなかったため作ってみました。	2021-08-14 00:39:54
海外TECH	DEV Community	Train a Deep Neural Network to recognize handwritten digits with Dannjs.	https://dev.to/matiasvlevi/train-a-deep-neural-network-to-recognize-handwritten-digits-with-dannjs-d5o	Train a Deep Neural Network to recognize handwritten digits with Dannjs A famous task performed by Deep models is handwritten digit recognition Here is how you can create your model amp train it with some images of digits RequirementsNodejsSome knowledge about neural networks Usingeasy mnistDannjsfs optional   MNISTWe re going to use a dataset called MNIST You can read more about it here MNIST is a dataset containing a total of x images of handwritten digits It contains an image and a label in order to identify the digit   MNIST to a Deep ModelTo show these images to our Deep model we re going to need to feed every pixel with values ranging in between and A would represent a black pixel and a would represent a white pixel The image below demonstrates this very well We could see a by image as an array of values This is how we are going to feed the images to our neural network When feeding our model with image data we also need to give the desired output in order to train it In the image above the neuron labeled is circled to demonstrate this  Now that we understand how we are going to train our MNIST model let s get started   Project setupStart by initiating an npm project withnpm init yIn order to access the dataset install the MNIST npm packagenpm i easy mnistWe are also going to install our Neural Network library Dannjs npm i dannjs  Import the datasetIn our index js file were going to require the dataset We are creating a training set of images and a testing set of images const dataset require easy mnist makeData This is going to create two sets the training set amp the testing set  Luckily our dataset of images already comes in length array format and the labels come as a length array We can access those like so For the training setdataset traindata index imagedataset traindata index label For the testing setdataset testdata index imagedataset testdata index label  Creating our ModelWe first need to create a model for this we are going to import dannjsconst Dann require dannjs dann We can then create a Dann model with inputs and outputs We re also going to add two hidden neuron layers with leakyReLU activations and then set the learning rate to const nn new Dann nn addHiddenLayer leakyReLU nn addHiddenLayer leakyReLU nn makeWeights nn lr We can then log the model to confirm the model creation was successfulnn log   Training the modelFor our model to be trained we need to iterate through the whole training set Having completed the entirety of the training set is what we call an epoch In order to successfully train a model we need multiple epochs  This is what epoch looks likefor let i i lt dataset traindata length i nn train dataset traindata i image dataset traindata i label We can then loop multiple epochslet epochs for let e e lt epochs e for let i i lt dataset traindata length i nn train dataset traindata i image dataset traindata i label console log Completed epoch e with a loss of nn loss With epochs depending on the model you created amp your CPU s performance it might take a few minutes epochs might not even be enough to train a very accurate model Around epochs your model might reach an acceptable level of accuracy The number of epochs amp training time all depend on a lot of factors about the model Experiment with the creation of a neural network try adding one more layer changing activation functions or changing the learning rate and see what happens Since it might take a while to train it is a good idea to save a model in order to keep training progress Here is how you can do so using fs do not forget to install it with npm i fs  Import fsconst fs require fs Saving our model to myModel jsonlet json JSON stringify nn toJSON fs writeFileSync myModel json json utf Loading back our model from myModel jsonlet data fs readFileSync myModel json utf let model JSON parse data const nn Dann createFromJSON model So there you have it How to train an MNIST model with Dannjs  We are hosting a MNIST model contest the most accurate model wins You can submit your model here amp try it out live Results are posted in our discord server here is the invite link	2021-08-13 15:07:00
Apple	AppleInsider - Frontpage News	Best Deals August 13 - $170 off internal SSD, $120 off Roborock Smart Vacuum, and more!	https://appleinsider.com/articles/21/08/13/best-deals-august-13---170-off-internal-ssd-120-off-roborock-smart-vacuum-and-more?utm_medium=rss	Best Deals August off internal SSD off Roborock Smart Vacuum and more Friday s best deals include off a Gigabyte Aero gaming laptop Mophie iPhone case deals iTunes movie deals and more Deals Friday August Shopping online for the best discounts and deals can be an annoying and challenging task So rather than sifting through miles of advertisements check out this list of sales we ve hand picked just for the AppleInsider audience Read more	2021-08-13 15:31:49
Apple	AppleInsider - Frontpage News	Exclusive: AirPods Max discounted to $449 this weekend	https://appleinsider.com/articles/21/08/13/exclusive-airpods-max-discounted-to-449-this-weekend?utm_medium=rss	Exclusive AirPods Max discounted to this weekendAirPods Max are discounted to this weekend exclusively for AppleInsider readers delivering the lowest price anywhere on the high end headphones AirPods Max dip to The AirPods Max deal is courtesy of Apple Authorized Reseller Adorama when activated with this pricing link and coupon code APINSIDER All five colors are eligible for the deal Read more	2021-08-13 15:03:49
海外TECH	Engadget	This week's best deals: $100 off the Apple Watch Series 6 and more	https://www.engadget.com/weekly-tech-deals-apple-watch-series-6-product-red-edition-mac-mini-m1-amazon-echo-devices-sale-154521347.html?src=rss	This week x s best deals off the Apple Watch Series and moreSamsung may have announced a bunch of new devices this week but it was Apple and Amazon that led the week when it came to online deals While Woot s flash sale on the Apple Watch Series Product Red Edition came and went quickly you can still get the smartwatch for at Amazon The Mac Mini M got a discount while a number of Echo devices went on sale as well ーincluding the new second generation Echo Show And through Sunday you can save on laptops tablets TVs and more in Best Buy s anniversary sale Here are the best tech deals from this week that you can still get today Apple Watch Series AppleThe Apple Watch Series Product Red Edition is off right now bringing it down to While not an all time low it s still a great deal on Apple s more powerful smartwatch We gave the Series a score of for its speedy performance improved battery life and faster charging However if you re willing to wait you ll be able to get the next generation Apple Watch pretty soon ーwe expect to see it debut sometime in September Buy Series Product Red at Amazon Mac Mini MEngadgetApple s Mac Mini M has returned to or off its normal price The sale price is actually but an automatically applied coupon will bring the final cost down even more This is the device to get if you want a compact desktop with the power and efficiency of Apple s M chipset Buy Apple Mac Mini GB at Amazon AirPods ProBilly Steele EngadgetApple s AirPods Pro remain off at Amazon bringing them down to These are the best sounding earbuds you can get from Apple and we gave them a score of for their better more secure fit IPX water resistance and solid audio quality Buy AirPods Pro at Amazon inch iPadApple s inch iPad is still on sale for or off its normal price It s arguably the best iPad for new tablet owners and we liked its improved performance familiar design and support for the first generation Apple Pencil Buy inch iPad at Amazon Beats Studio BudsBilly Steele EngadgetBeats new Studio Buds are off right now bringing them down to It s the first discount we ve seen on the buds since they came out a few months ago We gave them a score of for their smaller more comfortable design balanced sound and quick pairing on both Android and iOS Buy Beats Studio Buds at Amazon Amazon Echo devicesEngadgetA handful of Echo devices are on sale right now at Amazon including the second generation Echo Show for That s the best price we ve seen since the device came out earlier this year You can also grab the latest Echo Show for and the Echo Frames for Buy Echo Show at Amazon Buy Echo Show Kids at Amazon Buy Echo Show at Amazon Buy Echo Frames at Amazon Anova Precision Cooker NanoAnovaAnova s entry level sous vide machine the Nano remains discounted to It s a great option for those interested in giving sous vide cooking a try but don t want to spend a ton of money upfront to do so The Nano uses watts of power to cook food submerged in water and it can run for up to hours before it needs recharging Buy Anova Precision Cooker Nano at Amazon Buy Anova Precision Cooker Nano at Best Buy Comic Con sweepstakesThrough December you can enter to win four day passes to San Diego Comic Con Along with the passes you ll get access to a special preview night reserved seating in Hall H a personal concierge a private tour of the Comic Con Museum dinner in Balboa Park and tickets to the quot Night at the Comic Con Museum quot event It s free to enter but funds from this sweepstakes will go to the San Diego Comic Convention Enter to win at OmazeVirgin Galactic sweepstakesIn this Omaze giveaway you can win two seats on one of the first Virgin Galactic flights to space In addition you ll go on a tour of Spaceport America in New Mexico with Richard Branson You don t have to pay to enter but funds from all paid entries will support Space for Humanity an organization that hopes to make space more accessible for all Enter to win at OmazeGaming PC sweepstakesOmaze is giving away another to build your ultimate gaming PC This sweepstakes is free to enter but funds donated with purchased entries will benefit Schools on Wheels an organization that provides free tutoring and mentoring services to children experiencing homelessness across Southern California Enter to win at OmazePricing and availability is subject to change No donation or payment necessary to enter or win this sweepstakes See official rules on Omaze New tech dealsElgato Key Light AirElgato s slim Key Light Air has been a favorite of ours for streamers and now you can get it for or off its usual price It s a sleek LED panel with lumens that can provide just the right amount of light for your streams without taking up too much space It s also WiFi enabled so you can turn it on and off and switch up your light settings directly from your smartphone Buy Key Light Air at Amazon Instant Pot Duo Plus quart This in Instant Pot is off at Amazon thanks to a clippable coupon that knocks an additional off the sale price Along with pressure cooking you re getting rice cooking yogurt making steaming warming sous vide and other functions in this device plus a capacity large enough to make food for a big party Buy Instant Pot Duo Plus at Amazon Aukey Omnia Duo W Dual Port PD ChargerThis W GaN USB C charger from Aukey is only when you use the code OMNIADUO at checkout It includes two USB C ports so you can quickly power up two mobile devices at once or even your laptop and your smartphone simultaneously And because it uses GaN technology it s smaller than other similar chargers and isn t as susceptible to overheating Buy Omnia Duo W charger at Aukey NordVPNOne of our recommended VPNs is running a decent summer sale on a two year subscription You can sign up for NordVPN for for the first two years which comes out to per year and get three additional months of access for free We like NordVPN for its speed its no logs policy the thousands of servers it has to choose from and that one account supports up to six connected devices Buy NordVPN years Follow EngadgetDeals on Twitter for the latest tech deals and buying advice	2021-08-13 15:45:21
海外TECH	Engadget	Airbnb drops sexual harassment and assault arbitration rules for guests and hosts	https://www.engadget.com/airbnb-sexual-harassment-assault-forced-arbitration-guests-hosts-153010488.html?src=rss	Airbnb drops sexual harassment and assault arbitration rules for guests and hostsAirbnb will update its terms of service to drop arbitration provisions for sexual assault or harassment claims by guests or hosts The company expects the updated terms to be ready this fall quot We believe that survivors should be able to bring claims in whatever forum is best for them quot Airbnb wrote in a blog post quot We encourage our industry peers within the travel and hospitality space to consider taking similar steps for their respective communities quot The move will formalize Airbnb s current approach to such cases which it adopted in January The company hasn t asked a court to force sexual assault or harassment claims by hosts or guests into arbitration since then Nor will it do so until the updated terms of service are in effect quot Incidents of sexual assault are extremely rare on Airbnb but in these rare cases Airbnb s highly trained Safety team works with survivors to put their wellbeing first quot the company said According to the blog post members of its safety team have quot undergone training in trauma informed methodology and they prioritize supporting and empowering survivors in their healing process quot Airbnb didn t say whether it plans to change its arbitration rules for other types of harassment It ended forced arbitration for sexual harassment and assault claims by employees in late Other notable tech companies ditched forced arbitration for sexual assault and or harassment claims around that time including Uber Lyft Google and Square	2021-08-13 15:30:10
海外TECH	Engadget	Apple acknowledges 'confusion' over child safety updates	https://www.engadget.com/apple-on-confusion-over-child-safety-updates-csam-150121989.html?src=rss	Apple acknowledges x confusion x over child safety updatesApple is ready to acknowledge the controversy over its child safety updates but it sees this as a matter of poor messaging ーnot bad policy Senior software engineering VP Craig Federighi told the Wall Street Journal in an interview that introducing both the scans for child sexual abuse material CSAM on iCloud and opt in local monitoring of iMessage sexual content was a quot recipe for this kind of confusion quot People conflated the two and thought that Apple might spy on messages Federighi claimed adding that he wished Apple had quot come out a little more clearly quot The executive maintained that Apple was striking the right balance between child safety and privacy and addressed some of the concerns that surfaced since the company announced its new measures in early August He stressed that the scans of iCloud destined photos would only flag existing images in a CSAM database not any picture in your library The system only sends an alert when you reach a threshold of images so false positives aren t likely The system also has quot multiple levels of auditability quot Federighi said On device scanning will reportedly make it easier for researchers to check if Apple ever misused the technology Federighi also rejected the notion that the technique might be used to scan for other material such as politics noting that the database of images comes from multiple child safety groups not just the agency that will receive any red flag reports the National Center for Missing and Exploited Children The response won t satisfy those who object to the very notion that Apple is scanning photos on their phones even with privacy protections in place It is however a recognition that it can be a challenge to properly address privacy issues ーit doesn t take much to prompt an uproar	2021-08-13 15:01:21
金融	RSS FILE - 日本証券業協会	８月２１日（土）サーバメンテナンスのお知らせ	https://www.jsda.or.jp/shinchaku/servermaintenance/20210813155853.html	月日	2021-08-13 17:00:00
金融	ニュース - 保険市場TIMES	明治安田生命、高齢の加入者向けアフターフォローの取り組みを紹介	https://www.hokende.com/news/blog/entry/2021/08/14/010000		2021-08-14 01:00:00
ニュース	BBC News - Home	Plymouth shooting: Jake Davison was licensed gun holder	https://www.bbc.co.uk/news/uk-england-devon-58197414	davison	2021-08-13 15:39:29
ニュース	BBC News - Home	Afghanistan: Boris Johnson calls emergency meeting to discuss situation	https://www.bbc.co.uk/news/uk-58204857	labour	2021-08-13 15:45:20
ニュース	BBC News - Home	West Mercia Police officer and child found dead in Kidderminster	https://www.bbc.co.uk/news/uk-england-hereford-worcester-58205396	mercia	2021-08-13 15:42:45
ニュース	BBC News - Home	Covid: Who has to self-isolate, which workers are exempt and what if I'm fully vaccinated?	https://www.bbc.co.uk/news/explainers-54239922	august	2021-08-13 15:20:23
海外TECH	reddit	What is a thing many people hate but you absolutely love?	https://www.reddit.com/r/AskReddit/comments/p3mhn3/what_is_a_thing_many_people_hate_but_you/	What is a thing many people hate but you absolutely love submitted by u Clean Horror to r AskReddit link comments	2021-08-13 15:03:18
GCP	Cloud Blog	Partner Advantage two-year read out!	https://cloud.google.com/blog/topics/partners/google-cloud-partner-advantage-momentum/	Partner Advantage two year read out Last month marked the two year anniversary of Google Cloud Partner Advantage I want to thank our fast growing ecosystem of global partners for their hard work imagination and energized commitment and to reflect on how much we ve accomplished together In we kicked off by building a multi year action plan together with partners added some innovative Googleyness and have since remained laser focused on our core principles ensuring simplicity fostering collaboration focusing on the customer and sustaining a growth mindset  We also continue to measure partner success in three fundamental ways that set us apart in a highly competitive market Ensuring that Google Cloud and our partners are each aligned to the same business goals and strategies providing partners with the opportunities to earn and showcase their skills to the market and empowering partners to demonstrate differentiated value through customer success stories certifications Net Promoter Score newly added this year and more I am very pleased to share that to date the results have been fantastic thanks to an ecosystem based on trust and collaboration The average size of partner involved deals more than doubled from to We onboarded almost x more indirect resellers in the first three quarters of compared to the same period in Partner created pipeline in the mid market segment grew more than YoY from to Partners were involved in X more customer deals in than in The number of enterprise customer accounts with a partner attached increased by from to Our partner ecosystem has grown by more than in the last two years We ve rapidly expanded key programmatic elements of Partner Advantage such as incentives and Differentiation worked with analysts and partners to design the most compelling offerings integrated closely with key teams across Google Cloud advanced our technical infrastructure and deployed new features and growth drivers from our Partner Advisors to more formal certification and training options to portal features that bring greater control and transparency to partners  We ve also focused on ensuring that partners are part of every deal Resources such as the internal and external partner directories allow Google Cloud sales teams to match partners to deals help customers easily connect with the best partners for their needs and allow partners to showcase their expertise and knowledge depth  We highlight partner accomplishments by showcasing customer success stories expertise by industry or solution area and specialization in a major practice area all to make it easier for our customers to find the right partner at the right time with the right skills for innovation and confidence Check out the items below to learn more about what Partner Advantage has fueled and accomplished with our valued partners in the past two years Advancing the Partner Differentiation JourneyThe Google Cloud Partner Differentiation Journey has always been the heart and soul of Partner Advantage By providing partners with the tools training and insights they need to differentiate their business in a rapidly shifting global marketplace we help partners offer more value to customers In the two years since we launched Partner Advantage partners have looked to our Differentiation Journey to achieve their goals and win The number of Customer Success Stories published by partners has increased since More than are now online and accessible by customers  The number ofpartners with Specializations grew through Earning Specializations helps unlock additional benefits and incentives Our managed partners more than doubled their Expertise designations in over the prior year We ve also partnered with Forrester to take a deeper look at thebusiness opportunity Google Cloud offers to partners I d encourage you to read the report if you haven t already as it contains some excellent data and insights you won t find anywhere else Reinventing Partner Incentives Incentives are one of the most important elements of Partner Advantage and a strong motivator for partner loyalty and investment Since launch in our incentives portfolio has expanded significantly to offer partners more opportunities to earn and grow their business easier for partners to leverage and more competitive It s all about winning business with our partners ーtogether   In fact IDC is projecting that when you combine our incentives with other components of Partner Advantage the future looks very profitable The overall Google Cloud partner business opportunity is expected to increase by a factor of at least by On a global basis IDC expects partners to generate USD in revenue for every of Google Cloud revenue Better still they expect partner revenue to jump to for every dollar Google takes in by For our part the Google Cloud Partner Advantage incentives are an attractive competitive and comprehensive portfolio of rewards across Sell Service and Build partners Our partner investments include More than X increase in partner incentives and funds since launch  Google WorkspaceWe focused on rewarding partners for new customer acquisition and to protect partner investment which have led to more than a increase in win rate for partner registered deals and a significant increase in partner sourced pipeline  In we expanded the incentive portfolio to boost partner profitability for expanding into new markets and driving adoption leading to customer success We launched incentives for Distributors to expand into new geographies and new segmentsGoogle CloudBeginning with the MSP Initiative we ve expanded the incentives portfolio in to offer attractive partner discounts additional incentives for new customer acquisition and rewarding partners who help their customers grow consumption We have seen more partners utilizing the funding for pre sales engagements and deployments and for sales acceleration And in the summer of to expand our routes to market we launched Distribution incentives for GCP We re thrilled that our evolving resources and initiatives are strengthening our collaborative relationships with partners and helping to better serve our customers That relationship is the cornerstone to our strategy as we drive innovation and grow our businesses together To learn more about Google Cloud s partner program click here The Google Cloud Business Opportunity For Partners a commissioned Total Economic Impactstudy conducted by Forrester Consulting January  IDC eBook sponsored by Google Cloud Partner Opportunity in a Cloud World doc USBROI August	2021-08-13 16:00:00
GCP	Cloud Blog	A technical solution producing highly-personalized investment recommendations using ML	https://cloud.google.com/blog/topics/financial-services/softserve-uses-google-cloud-to-improve-retail-investing/	A technical solution producing highly personalized investment recommendations using MLDeveloped by SoftServe with the use of Google Cloud the Investment Products Recommendation Engine IPRE is a solution designed to tackle common retail banking customer investment challenges In particular it makes investment recommendations based on BigQuery ML model capabilities Big data pipelines are utilized to process investment data The environment setup is automated with the use of Terraform In this blog post we will take a closer look at the technical implementation of the solution  Solution architectureLet s dive deeper into the technical part of the solution and consider solution architecture Components of the pattern architecture are split into three main areas shown in Figure Figure Investment product recommendation engine solution architectureThe Web UI area is indicated by the green color and corresponds to the web application React js application deployed in Cloud Run The application demonstrates features of investment risk preferences and portfolio investment recommendations The web application has its database to respond to users requests The Data processing area is indicated by the beige color and corresponds to the Data Processing that performs data transformation aggregation and putting the data into a BigQuery data lake That part includes fetching data from external sources Yahoo Finance is used as sample data storing raw data in Cloud Data Storage transforming data with the use of Cloud Dataflow and putting data into BigQuery The data pipeline is orchestrated by Cloud Composer The Recommendation Engine area is indicated by the pink color and corresponds to the Recommendation Engine RE The RE provides portfolio optimization data for incoming requests from the web application AutoML Tables models are used to make two different predictions Investor risk preferencesInvestment recommendationsThe solution is deployed on Google Cloud Terraform is used to set up all required components and establish the right communications between them IPRE workflowThe following steps are executed to provide users with investment recommendations based on their risk preferences The Investor Risk Preference cloud function generates users synthetic data and their preferences Capital Market Data is fetched from Yahoo Finance by the Cap Market cloud function and stored as raw data in Cloud Storage When new raw data is available in the bucket the Cloud Dataflow job orchestrated by Cloud Composer is triggered Dataflow stores processed data in BigQuery BigQuery Training AutoML jobs which are orchestrated by Cloud Composer are triggered after initial setup or daily and create the corresponding BigQuery ML Models Based on available data BigQuery AutoML generates potential Investor risk preference profiles and investment recommendations and puts it into Cloud Storage The risk preference profile is determined for the user that signed in to the Web Application The recommendations are displayed based on the user s investment profile A separate UI Fulfillment backend service provides recommended data to the user Each day when new capital market data is available investment portfolio recommendations are updated with the same flow Data pipelinesThe IPRE service relies on multiple data sources both internal and external The solution implements scalable data pipelines with technologies such as BigQuery Cloud Storage and Dataflow All external raw data streams are aggregated in dedicated Cloud Storage buckets The Cloud Functions trigger minor pre processing scripts Writing an object to the Cloud Storage bucket triggers a Dataflow job for adding new data to BigQuery This type of architecture makes an ETL pipeline resilient to corrupt data and scalable to multiple data sources The Cloud Functions provide a clean cost effective solution for migrating massive datasets from data lake to DWH Capital markets dataHistorical market data is a crucial element for the recommendation service A dedicated data pipeline job collects quotes of the selected securities from Yahoo Finance All selected assets vary in return and risk This allows IPRE to construct a wide range of portfolios to meet diverse investors preferences After minor preprocessing daily historical quotes q are turned into periodic returns Returns of observations with a unique timestamp are written to Cloud Storage It allows reducing egress and ensures that BigQuery does not receive duplicate data During the first run of the script all observations starting from will make it to BigQuery  Subsequent runs provide incremental observations of the unseen data In the final stage of ETL the processed data is written to BigQuery Aggregating data in BigQuery allows other services to retrieve the data in a cost effective way Investors risk preferencesThe investor risk preferences IRP are a synthetic dataset containing historical records of thousands of existing retail investors This dataset is a crucial component for making personalized recommendations based on an individual s investment preferences  The risk aversion is a target variable of interest Average monthly income education loans and deposits are among independent variables Investors attributes are generated using different continuous variable distribution functions Gamma Gumbel Gaussian R distributed and others A script produces monthly snapshots of investors attributes resulting in data points  The Cloud Function triggers a generation of the dataset upon the first launch of IPRE Dataflow migrates the generated dataset from Cloud Storage to BigQuery Machine learning advanced analyticsThe machine learning ML workflow is as follows Raw data is preprocessed and uploaded to GCS A Dataflow job is registered through Google Composer  Processed data is uploaded to BigQuery with predefined data schema and data format By the Pub Sub trigger training of AutoML and ARIMA models is triggered The training is performed with the use of integrated BigQuery ML tools When the training has completed the system triggers the inference process  Individual risk preferences and ticker s prices are predicted by taking the uploaded BigQuery data as an input Predicted results are saved to Cloud Storage to cache the results and make the data reusable Results are published through the recommendation engine which is deployed on Cloud Run and prediction results are sent to the end user The workflow is shown in Figure Figure Machine learning workflowIPRE implementation featuresThe solution is designed to be highly reproducible with the minimal manual effort required to set up all services Users of the web application can create several wallets and switch among them In addition to working with wallets users can see investment recommendations and their portfolio with detailed statistics The application s back end is a service developed using Django Framework The service which acts as a bridge between the IPRE and the web application is responsible for working with wallets managing transactions showing user portfolio The ML interface pipeline is designed with ease of deployment in mind so that the solution can be deployed on Google Cloud with just one click Better investing with IPREUsing Google Cloud Platform SoftServe developed the IPRE solution and within the solution implemented an end to end automated MLmodel that can be deployed in one click SoftServe s Investment Products Recommendation Engine serves as a pivotal point in increasing the cross selling potential of investment products to retail banking customers It establishes a bridge between retail banking investors who are non finance professionals and the complexity of modern capital markets investment vehicles The solution applies ML technology for micro segmentation of user groups based on their risk preferences to provide highly personalized investment products selection to an individual user The IPRE makes investment recommendations based on BigQuery ML Model capabilities and uses Big Data pipelines to process investment data The environment setup is automated by Terraform The solution incorporates a fully automated ML process Extensive pattern automation will help developers easily switch to implementation and explore different configuration options If you want to dive deeper into the solution or implement your own IPRE with the use of GCP please check out the pattern details or reach out to the Google Cloud or SoftServe team to get more information Related ArticleRegistration is open for Google Cloud Next October Register now for Google Cloud Next on October Read Article	2021-08-13 16:00:00
GCP	Cloud Blog	Solving Banking challenges with highly personalized investment recommendations using AI	https://cloud.google.com/blog/topics/financial-services/softserve-makes-investing-easier-with-google-cloud/	Solving Banking challenges with highly personalized investment recommendations using AIData science is one of today s key priorities for finance industry leaders Data Scientists harness knowledge to draw meaning from data to turn data into information and to translate information into practical insights that will bring a better understanding of how to gain customer loyalty minimize churn and grow revenue In this blog post we will look at a comprehensive investment banking solution that builds a bridge between retail investors and the complexity of the capital markets Let s explore how Google Cloud Data and Analytics services can be used to turn real time insight into an automated process creating frictionless digital experiences to help retail investors with little capital markets expertise The solution developed by SoftServe provides users with personalized investment recommendations to help make better decisions Called the Investment Products Recommendation Engine IPRE SoftServe designed this solution to recommend the most suitable investment product by balancing an individual s risk preferences and expected return on investment SoftServe s IPRE collects and processes market data e g quotes daily or weekly open high low close prices on available investment products such as stocks bonds powered by BigQuery and Cloud Functions The IPRE prepares the raw data via Dataflow and constructs an optimal mean variance portfolio for a given level of risk So the investment portfolio is optimized to provide the highest expected return on investment for a given risk level An investor s risk appetite depends on various factors and may exhibit non stationary evolution over time To produce recommendations in accordance with the optimal risk level for an individual investor SoftServe used an AutoML Tables model based on a variety of customer characteristics level of income level of savings level of education employment geography etc This approach provides more flexibility when compared to classical investment theory metrics such as Constant Relative Risk Aversion “CRRA Constant Absolute Risk Aversion “CARA etc consequently enabling the IPRE to unlock new customer segments Finally after providing recommendations for a portfolio of optimal assets based on risk levels the IPRE estimates the qualitative and quantitative characteristics of the portfolio It computes sophisticated industry grade investment metrics describing the marginal risks Conditional Value at Risk CVaR diversification effects Sharpe Ratio sensitivity of the portfolio to market fluctuations etc Let s take a look at a hypothetical user journey to better understand the purpose of the solution and the value it brings to market  Meet Felix a year old architect whose dream is to buy his own flat in the next five years He realizes he must accumulate more savings A few months ago Felix opened an account in the For the Future bank because of the smart investment feature on their mobile app where he receives investment recommendations and can make decisions on the go Felix has set a financial goal and built up a portfolio of investment funds aligned with his risk tolerance and his investment goals One day on his way to work Felix receives a personalized investment recommendation from the For the Future bank s mobile app The app is constantly working to help Felix reach his goal and does all the time consuming work on collecting and processing market data The machine learning model generates recommendations such as expected rate of return popularity of the asset among people with portfolios like Felix s and information about the risk level that matches Felix s portfolio Felix can use that information to make a decision The process of using the app was quick and simple Felix s portfolio gets automatic updates with the total value of the portfolio and tracks its performance against his financial goals Felix continues his way to work smiling to himself knowing that he is a little bit closer to owning his dream home The technical implementation of the solution in Google Cloud incorporates Dataflow batch processing pipelines as well as trained investment recommendation Big Query Machine Learning “BQML models and data analytic services such as BigQuery Cloud Storage and Pub Sub The solution is described in the blog post How to implement an Investment Product Recommendation solution in GCP In partnership with Google Cloud SoftServe helps our clients solve complex problems with innovative solutions to achieve a faster time to market increase ROI and provide great user experiences To gain a broader understanding of the solution and see how its architecture works in real life watch SoftServe s user journey presented at Google Southeast Asia Financial Services Cloud OnAir Creating aha moments in Financial Services	2021-08-13 16:00:00
GCP	Cloud Blog	Verify GKE Service Availability with new dedicated uptime checks	https://cloud.google.com/blog/products/operations/verify-gke-services-are-up-with-dedicated-uptime-checks/	Verify GKE Service Availability with new dedicated uptime checksKeeping the experience of your end user in mind is important when developing applications Observability tools help your team measure important performance indicators that are important to your users like uptime It s generally a good practice to measure your service internally via metrics and logs which can give you indications of uptime but an external signal is very useful as well wherever feasible  One of the easiest ways to measure your services externally is to use an established and trusted technology an uptime check Uptime checks closely monitor the availability of your service and can serve as a leading indicator of a problem This can hopefully help you reduce or eliminate the time an issue affects your users  Uptime checks for GKE services With the proliferation of the microservices architecture more services means more endpoints to measure Trying to track isolate and resolve issues can be increasingly complex That s why we re excited to introduce the new uptime check for Google Kubernetes Engine GKE LoadBalancer services  Google Cloud has offered uptime checks for different types of resources but none of these provided a direct association with GKE With our new integration the GKE LoadBalancer uptime check directly associates a service load balancer with an uptime check helping to ensure the uptime check is managed dynamically As the underlying network for a service changes the uptime check changes with it allowing you to quickly correlate a service with an uptime failure  You can also set up an alert policy based on your uptime check allowing your SRE or Ops team to be notified of a meaningful issue that s impacting your service Once notified you can jump straight into the associated GKE Dashboard to better isolate the root cause  Creating a new uptime checkTo get started you can head to Monitoring gt Uptime and select “ Create Uptime Check and then select the new Kubernetes Loadbalancer Service option More informationVisit our documentation for Managing uptime checks where you can get additional information and step by step instructions for creating your first uptime check Lastly if you have questions or feedback about this new feature head to the Cloud Operations Community page and let us know	2021-08-13 16:00:00