data-newsletter-4 recommender-systems
Lessons from the Netflix Prize: Changing Requirements and Cost-Effectiveness
04 Sep 2017 Netflix never really used the #1 winning solution to the Netflix Challenge. Some of the reasons were that just wasn't cost-effective to implement the full thing and another was that requirements had changed.
Read More ›data-newsletter-4 kaggle data-science
Winning Solutions Overview: Kaggle Instacart Competition
04 Sep 2017 The Instacart "Market Basket Analysis" competition focused on predicting repeated orders based upon past behaviour. Among the best-ranking solutings, there were many approaches based on gradient boosting and feature engineering and one approach based on end-to-end neural networks.
Read More ›technology data-newsletter-4 machine-learning
A Quick Summary of Ensemble Learning Strategies
01 Sep 2017 Ensemble learning refers to mixing the outputs of several classifiers in various ways, so as to get a better result than each classifier individually.
Read More ›technology data-newsletter-4 machine-learning model-evaluation
Evaluation Metrics for Classification Problems: Quick Examples + References
31 Aug 2017 There are multiple ways to measure your model's performance in machine learning, depending upon what objectives you have in mind. Some of the most important are Accuracy, Precision, Recall, F1 and AUC.
Pandas for Large Data: Examples and Tips
13 Aug 2017 In order to successfully work with large data on Pandas, there are some ways to reduce memory usage and make sure you get good speed performance.
Read More ›Suggestions on how to make LinkedIn more relevant
04 Aug 2017 LinkedIn is a nice platform for connecting to professional peers but its real value lies, in my opinion, in its potential to the the global professional rating system. But it needs some improvement.
technology reminder hierarchy clustering
Quick Reminder: Clustering
29 Jul 2017 Quick reminder on key points regarding clustering (hierarchical and otherwise)
Read More ›Install NodeJS and NPM on Ubuntu
28 Jul 2017 Installing the latest NPM + NodeJS on Ubuntu
Read More ›Python Pickle: examples and reference
12 Jul 2017 Pickle is a well-known Python tool for saving arbitrary variable contents into file. Here are a couple of examples and tips on how you can use it to make your data science work more efficient and easily reproducible.
Read More ›technology codebuild codepipeline docker beanstalk continuous-integration continuous-deployment
Using AWS CodePipeline to Automatically Deploy and Build your App Stored on Github as a Docker-based Beanstalk Application
07 Jul 2017 A full guide on how to set up a continuous deployment pipeline using GitHub and AWS CodePipeline, in order to deploy a Docker-based Beanstalk Application.