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 (33)

• Binary Classification with Automated Machine Learning - 17 May 2021
  
  Check out how to use the open-source MLJAR auto-ML to build accurate models faster.
• A Comprehensive Guide to Ensemble Learning – Exactly What You Need to Know - 06 May 2021
  
  This article covers ensemble learning methods, and exactly what you need to know in order to understand and implement them.
• Gradient Boosted Decision Trees – A Conceptual Explanation - 30 Apr 2021
  
  Gradient boosted decision trees involves implementing several models and aggregating their results. These boosted models have become popular thanks to their performance in machine learning competitions on Kaggle. In this article, we’ll see what gradient boosted decision trees are all about.
• 10 Real-Life Applications of Reinforcement Learning - 12 Apr 2021
  
  In this article, we’ll look at some of the real-world applications of reinforcement learning.
• The Best Machine Learning Frameworks & Extensions for TensorFlow - 05 Apr 2021
  
  Check out this curated list of useful frameworks and extensions for TensorFlow.
• The Best Machine Learning Frameworks & Extensions for Scikit-learn - 22 Mar 2021
  
  Learn how to use a selection of packages to extend the functionality of Scikit-learn estimators.
• 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.