Alternatives to Amazon Rekognition

Google Analytics is a great tool to analyze your traffic. To debug our software and ask questions, we love to use Postman and Stack Overflow. Google Drive helps our team to share documents. We're able to build our great products through the APIs by Google Maps, CloudFlare, Stripe, PayPal, Twilio, Let's Encrypt, and TensorFlow.

Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details—for instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA’s CUDA toolkit.

Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo’s deep learning toolkit which makes it easier to start—and speed up—distributed deep learning projects with TensorFlow:

https://eng.uber.com/horovod/

(Direct GitHub repo: https://github.com/uber/horovod)

Hi Team,

Could you please suggest which one need to be used in between OpenCV and FFMPEG.

Thank you in Advance.

Google Analytics is a great tool to analyze your traffic. To debug our software and ask questions, we love to use Postman and Stack Overflow. Google Drive helps our team to share documents. We're able to build our great products through the APIs by Google Maps, CloudFlare, Stripe, PayPal, Twilio, Let's Encrypt, and TensorFlow.

I created a simple upload/download functionality for a web application and connected it to Mongo, now I can upload, store and download files. I need advice on how to create a SPA similar to Dropbox or Google Drive in that it will be a hierarchy of folders with files within them, how would I go about creating this structure and adding this functionality to all the files within the application?

Intuitively creating a react component and adding it to a File object seems like the way to go, what are some issues to expect and how do I go about creating such an application to be as fast and UI-friendly as possible?

Google Analytics is a great tool to analyze your traffic. To debug our software and ask questions, we love to use Postman and Stack Overflow. Google Drive helps our team to share documents. We're able to build our great products through the APIs by Google Maps, CloudFlare, Stripe, PayPal, Twilio, Let's Encrypt, and TensorFlow.

When I first built my portfolio I used GitHub for the source control and deployed directly to Netlify on a push to master. This was a perfect setup, I didn't need any knowledge about #DevOps or anything, it was all just done for me.

One of the issues I had with Netlify was I wanted to gzip my JavaScript files, I had this setup in my #Webpack file, however Netlify didn't offer an easy way to set this.

Over the weekend I decided I wanted to know more about how #DevOps worked so I decided to switch from Netlify to Amazon S3. Instead of creating any #Git Webhooks I decided to use Buddy for my pipeline and to run commands. Buddy is a fantastic tool, very easy to setup builds, copying the files to my Amazon S3 bucket, then running some #AWS console commands to set the content-encoding of the JavaScript files. - Buddy is also free if you only have a few pipelines, so I didn't need to pay anything 🤙🏻.

When I made these changes I also wanted to monitor my code, and make sure I was keeping up with the best practices so I implemented Code Climate to look over my code and tell me where there code smells, issues, and other issues I've been super happy with it so far, on the free tier so its also free.

I did plan on using Amazon CloudFront for my SSL and cacheing, however it was overly complex to setup and it costs money. So I decided to go with the free tier of CloudFlare and it is amazing, best choice I've made for caching / SSL in a long time.

I created a simple upload/download functionality for a web application and connected it to Mongo, now I can upload, store and download files. I need advice on how to create a SPA similar to Dropbox or Google Drive in that it will be a hierarchy of folders with files within them, how would I go about creating this structure and adding this functionality to all the files within the application?

Intuitively creating a react component and adding it to a File object seems like the way to go, what are some issues to expect and how do I go about creating such an application to be as fast and UI-friendly as possible?

Anyone recommend a good connector like Kloudless for connecting a SaaS app to Dropbox/Box etc? Cheers

StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

Future improvements / technology decisions included:

Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

When my SSL cert MaxCDN was expiring on my personal site I decided it was a good time to revamp some things. Since GitHub Services is depreciated I can no longer have #CDN cache purges automated among other things. So I decided on the following: GitHub Pages, Netlify, Let's Encrypt and Jekyll. Staying the same was Bootstrap, jQuery, Grunt & #GoogleFonts.

What's awesome about GitHub Pages is that it has a #CDN (Fastly) built-in and anytime you push to master, it purges the cache instantaneously without you have to do anything special. Netlify is magic, I highly recommend it to anyone using #StaticSiteGenerators.

For the most part, everything went smoothly. The only things I had issues with were the following:

• If you want to point www to GitHub Pages you need to rename the repo to www
• If you edit something in the _config.yml you need to restart bundle exec jekyll s or changes won't show
• I had to disable the Grunt htmlmin module. I replaced it with Jekyll layout that compresses HTML for #webperf

Last but certainly not least, I made a donation to Let's Encrypt. If you use their service consider doing it too: https://letsencrypt.org/donate/

We migrated the hosting of our CDN, which is used to serve the JavaScript Error collection agent, from Amazon CloudFront to MaxCDN. During our test, we found MaxCDN to be more reliable and less expensive for serving he file.

The reports and controls were also considerably better.