About Derrick Mwiti

Derrick Mwiti is a data scientist who has a great passion for sharing knowledge. He is an avid contributor to the data science community via blogs such as Heartbeat, Towards Data Science, Datacamp, Neptune AI, KDnuggets just to mention a few. His content has been viewed over a million times on the internet. Derrick is also an author and online instructor. He also trains and works with various institutions to implement data science solutions as well as to upskill their staff. Derrick’s studied Mathematics and Computer Science from the Multimedia University, he also is an alumnus of the Meltwater Entrepreneurial School of Technology. If the world of Data Science, Machine Learning, and Deep Learning interest you, you might want to check his Complete Data Science & Machine Learning Bootcamp in Python course.

Derrick Mwiti Posts (27)

• Pruning Machine Learning Models in TensorFlow - 04 Dec 2020
  
  Read this overview to learn how to make your models smaller via pruning.
• Deploying Trained Models to Production with TensorFlow Serving - 30 Nov 2020
  
  TensorFlow provides a way to move a trained model to a production environment for deployment with minimal effort. In this article, we’ll use a pre-trained model, save it, and serve it using TensorFlow Serving.
• Dealing with Imbalanced Data in Machine Learning - 29 Oct 2020
  
  This article presents tools & techniques for handling data when it's imbalanced.
• Feature Ranking with Recursive Feature Elimination in Scikit-Learn - 19 Oct 2020
  
  This article covers using scikit-learn to obtain the optimal number of features for your machine learning project.
• Fast Gradient Boosting with CatBoost - 16 Oct 2020
  
  In this piece, we’ll take a closer look at a gradient boosting library called CatBoost.
• Machine Learning in Dask - 22 Jun 2020
  
  In this piece, we’ll see how we can use Dask to work with large datasets on our local machines.
• LightGBM: A Highly-Efficient Gradient Boosting Decision Tree - 18 Jun 2020
  
  LightGBM is a histogram-based algorithm which places continuous values into discrete bins, which leads to faster training and more efficient memory usage. In this piece, we’ll explore LightGBM in depth.
• Federated Learning: An Introduction - 15 Apr 2020
  
  Improving machine learning models and making them more secure by training on decentralized data.
• TensorFlow Dev Summit 2020: Top 10 Tricks for TensorFlow and Google Colab Users - 08 Apr 2020
  
  In this piece, we’ll highlight some of the tips and tricks mentioned during this year’s TF summit. Specifically, these tips will help you in getting the best out of Google’s Colab.
• Research Guide for Depth Estimation with Deep Learning - 12 Nov 2019
  
  In this guide, we’ll look at papers aimed at solving the problems of depth estimation using deep learning.