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 (10)

• 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.
• Object Detection with Luminoth - 13 Mar 2019
  
  In this article you will learn about Luminoth, an open source computer vision library which sits atop Sonnet and TensorFlow and provides object detection for images and video.
• Using Caret in R to Classify Term Deposit Subscriptions for a Bank - 04 Feb 2019
  
  This article uses direct marketing campaign data from a Portuguese banking institution to predict if a customer will subscribe for a term deposit. We’ll be working with R’s Caret package to achieve this.
• Automated Machine Learning in Python - 18 Jan 2019
  
  An organization can also reduce the cost of hiring many experts by applying AutoML in their data pipeline. AutoML also reduces the amount of time it would take to develop and test a machine learning model.
• 2018 Year-in-Review: Machine Learning Open Source Projects & Frameworks - 17 Dec 2018
  
  This post is a look at the top open source projects and major developments in machine learning frameworks over the past 12 months.
• Sales Forecasting Using Facebook’s Prophet - 28 Nov 2018
  
  In this tutorial we’ll use Prophet, a package developed by Facebook to show how one can achieve this.
• Introduction to PyTorch for Deep Learning - 07 Nov 2018
  
  In this tutorial, you’ll get an introduction to deep learning using the PyTorch framework, and by its conclusion, you’ll be comfortable applying it to your deep learning models.
• Introduction to Deep Learning with Keras - 29 Oct 2018
  
  In this article, we’ll build a simple neural network using Keras. Now let’s proceed to solve a real business problem: an insurance company wants you to develop a model to help them predict which claims look fraudulent.
• Beginner Data Visualization & Exploration Using Pandas - 22 Oct 2018
  
  This tutorial will offer a beginner guide into how to get around with Pandas for data wrangling and visualization.