About Derrick Mwiti

Derrick Mwiti is a Data Scientist with expertise in machine learning, data analytics, and visualization. He enjoys working with data to derive meaningful insights that help business executives in decision making. He is an alumnus of the prestigious Meltwater Entrepreneurial School of Technology(MEST). Derrick is an avid contributor to the data science community. He does so by contributing to popular data science publications such as KDnuggets, Heartbeat, and Datacamp just to mention a few. He holds a Bachelor of Science in Mathematics and Computer Science from Multimedia University.

Derrick Mwiti Posts (22)

• 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.
• Research Guide: Advanced Loss Functions for Machine Learning Models - 06 Nov 2019
  
  This guide explores research centered on a variety of advanced loss functions for machine learning models.
• Research Guide for Transformers - 30 Oct 2019
  
  The problem with RNNs and CNNs is that they aren’t able to keep up with context and content when sentences are too long. This limitation has been solved by paying attention to the word that is currently being operated on. This guide will focus on how this problem can be addressed by Transformers with the help of deep learning.
• Research Guide for Video Frame Interpolation with Deep Learning - 15 Oct 2019
  
  In this research guide, we’ll look at deep learning papers aimed at synthesizing video frames within an existing video.
• Research Guide for Neural Architecture Search - 04 Oct 2019
  
  In this guide, we will explore a range of research papers that have sought to solve the challenging task of automating neural network design.
• A 2019 Guide for Automatic Speech Recognition - 24 Sep 2019
  
  In this article, we’ll look at a couple of papers aimed at solving the problem of automated speech recognition with machine and deep learning.