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 (18)

• 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.
• A 2019 Guide to Speech Synthesis with Deep Learning - 09 Sep 2019
  
  In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.
• A 2019 Guide to Human Pose Estimation - 28 Aug 2019
  
  Human pose estimation refers to the process of inferring poses in an image. Essentially, it entails predicting the positions of a person’s joints in an image or video. This problem is also sometimes referred to as the localization of human joints.
• A 2019 Guide to Semantic Segmentation - 12 Aug 2019
  
  Semantic segmentation refers to the process of linking each pixel in an image to a class label. These labels could include a person, car, flower, piece of furniture, etc., just to mention a few. We’ll now look at a number of research papers on covering state-of-the-art approaches to building semantic segmentation models.
• A 2019 Guide to Object Detection - 01 Aug 2019
  
  Object detection has been applied widely in video surveillance, self-driving cars, and object/people tracking. In this piece, we’ll look at the basics of object detection and review some of the most commonly-used algorithms and a few brand new approaches, as well.