Data Science

Good News for all Python Developers and Data Scientists — Anaconda has been offering an open source distribution of the Python and R programming languages and complementary development tools with a focus on Data Scientists for some time (some versions free of charge). Now Anaconda wants to push the work with Python in the browser and the cloud. In addition…

Following these rules has drastically improved my effectiveness as a data scientist to deliver more value from my work — Being An Effective Data Scientist is Hard It’s 08:55, Monday morning, late 2016. I’ve just walked into the office of my first ‘official’ data science job. I’ve done the doctorate, I’ve learnt the maths and stats, I’ve taught myself Python and SQL, been through Andrew Ng’s machine learning course, and practised my random forests and clustering. I…

Make Working with NumPy Even Better — NumPy is one of the quintessential data science libraries available in Python. Being able to work with it effectively can make your day-to-day work much, much easier. The four tips you’ll learn in this tutorial will give you much greater control over how the library works and what you can…

As businesses grow, so too does their data requirements. Large organizations now have more data than they know what to do with. This data can be challenging to process and analyze, especially when you need to process it in real time. Kafka is a distributed messaging system that’s specifically designed…

One of the first applications of transformer models to video intelligence. — I recently started an AI-focused educational newsletter, that already has over 125,000 subscribers. TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Please give…

How to use Topline Impact to measure and compare Experiment Results — Positive results in an experiment are one of the highlights in an analyst’s day-to-day work (and equally so for the product team). Seeing a key metric move significantly in the desired direction is a great reward for the all the hard work that goes into an experiment…

How I improved speed by 10x — Recently, I’ve been working on an anomaly detection model for a project at work. I needed to improve the speed of my code by 10x. In this post, I’ll describe how I achieved this goal and some of the challenges I encountered along the way. Roughly speaking, anomaly detection techniques…

Integrate modules from imblearn, feature-engine in your pipeline, and extract feature importance plots — Using pipelines in your machine learning project helps you bring more structure to your workflow. They make your different process steps easier to understand, reproducible and prevent data leakage. Scikit-learn pipeline(s) work great with its transformers, models, and other modules. However, it can be (very) challenging when one tries to…