"Garbage in, garbage out" is true in Machine Learning. The success of any ML model hinges on the quality of the data fed into it. Clean, well-prepared data not only enhances the performance of models but also ensures reliable and accurate predictions.
The Importance of Clean Data
1. Improved...
There are three common machine learning algorithms: Linear Regression, Decision Trees, and K-Nearest Neighbors (KNN). Each of these algorithms offers unique capabilities and applications, making them invaluable tools in the machine learning toolkit.
Linear Regression
Overview: Linear regression...
This week I began to explore Machine Learning Probability:
Understanding Machine Learning Probability
At the core of machine learning lies the concept of probability, which forms the bedrock of various algorithms and models. Let's dissect some essential probability distributions and their...
Delving into the realm of machine learning has been an enlightening journey for me, and I've made it a point to document my discoveries as I progress. Last week, I embarked on several introductory courses that laid the groundwork for understanding the essentials of machine learning. In this blog...
As I am diving into machine learning, I am documenting my findings along the way. Last week, I took several introductory courses, and I was able to grasp the following basics of machine learning. Let's explore these fundamental concepts and their applications in the ever-evolving world of...
As someone looking to break into leadership AI roles, I had several conversations with Machine Learning Engineers and AI Product Owners to identify key topics to cover and courses that would be beneficial. Majority of these courses will be LinkedIn Learning courses because I get access to...
I have been in the Tech world for over a decade. I’ve been a business analyst, scrum master, project manager, management consultant, and a Director of Tech. But the exponential growth of A.I. has made me feel like a beginner again. I have just started to scratch the surface of what that...
