Introduction

MLOps is one if the most popular buzzwords in Machine Learning and Data Science at the moment, but one of the areas least covered by online courses, YouTube videos and bootcamps.

You can read up on how I define MLOps at home here:

Since writing the above article, I have…

Data to support your search for the next meme stock.

Introduction

Financial data is the backbone of modern Hedge Funds, Banks, FinTechs and many others. These organisations typically have plenty of cash and are able to spend it on data, hence financial data often fetches a hefty price tag.

As a…

Introduction

As we know, Machine Learning is ubiquitous in our day to day lives. From product recommendations on Amazon, targeted advertising, and suggestions of what to watch, to funny Instagram filters.

If something goes wrong with these, it probably won’t ruin your life. …

Introduction

Gradient Boosting models such as XGBoost, LightGBM and Catboost have long been considered best in class for tabular data. Even with rapid progress in NLP and Computer Vision, Neural Networks are still routinely surpassed by tree-based models on tabular data.

Enter Google’s TabNet in 2019. According to the paper, this…

Introduction

Linear Models are considered the Swiss Army Knife of models. There are many adaptations we can make to adapt the model to perform well on a variety of conditions and data types.

Generalised Additive Models (GAMs) are an adaptation that allows us to model non-linear data while maintaining explainability.

Table of Contents

• What…

Introduction

Over the past few years, many organisations have found that although they train great models, they don’t always gain long-term value from them. The reason for this is deployment and monitoring.

Deploying a model isn’t always that easy. Sometimes they are large. How long does inference take? You might need…

Introduction

Data Science is still a roaring field with demand continuing to outstrip supply and many business expecting to increase their IT spend drastically over the next few years.

Although there has been a sharp rise in online courses, bootcamps and degrees and with them, an increase in junior talent, it…

Introduction

When I first started learning Data Science and looking at projects, I thought you could either do a Deep Learning or regular project. This is not the case.

With powerful models becoming more and more accessible, we can easily leverage some of the power of deep learning without having to…