Hi! Welcome to My Blog. I’m Victor Omondi, a Data Analyst at Maisha Meds, A Computer Technology graduate from Multimedia University of Kenya. I like manipulating, exploring, visualizing and modeling data to obtain insights that can be used in future decision making.

### Hyperparameter Tuning with Python

perform hyperparameter tuning techniques to your most accurate model in an effort to achieve optimal predictions.

### A Quick Tour of Variables and Data Types in Python

This tutorial is the second in a series on introduction to programming using the Python language. These tutorials take a practical coding-based approach, and the best way to learn the material is to execute the code and experiment with the examples.

### Cluster Analysis in R

build a strong intuition for how they work and how to interpret hierarchical clustering and k-means clustering results

### Cluster Analysis in Python

exploring unsupervised learning through clustering using the SciPy library in Python

### Analyzing Hacker News Dataset

### Working with Missing Data

we’ll handle missing data without having to drop rows and columns using data on motor vehicle collisions released by New York City and published on the NYC OpenData website. There is data on over 1.5 million collisions dating back to 2012, with additional data continuously added. We’ll work with an extract of the full data: Crashes from the year 2018.

### Working With Dates and Times in Python

How to work with Dates and Times in python

### Unsupervised Learning in Python

Unsupervised learning encompasses a variety of techniques in machine learning, from clustering to dimension reduction to matrix factorization. In this blog, we’ll explore the fundamentals of unsupervised learning and implement the essential algorithms using scikit-learn and scipy.

### Supervised Learning with scikit-learn

Supervised learning, an essential component of machine learning. We’ll build predictive models, tune their parameters, and determine how well they will perform with unseen data—all while using real world datasets. We’ll be learning how to use scikit-learn, one of the most popular and user-friendly machine learning libraries for Python.

### Statistical Thinking in Python (Part 2)

Expanding and honing hacker stats toolbox to perform the two key tasks in statistical inference, parameter estimation and hypothesis testing.