10 Must-Read Machine Learning Articles for Beginners
Machine Learning, the branch of Artificial Intelligence (AI) has taken the world by storm in recent years. Thanks to the ever-increasing processing power of the computers and the abundance of data available, Machine Learning has become one of the most popular and exciting fields of study today. Whether you are an IT professional, Data analyst, or just someone interested in the topic, the following 10 must-read machine learning articles for beginners will help you get started on your journey.
1. What is Machine Learning? An Introduction
Machine Learning is a complex field of study that revolves around algorithms and data models. This article lays down the preliminary understanding of Machine Learning, types of algorithms, and how it can benefit you.
2. The Basics of Machine Learning -Cheat Sheet
If you are looking for a quick reference guide to the basics of Machine Learning, this article is for you. It provides a concise summary of the fundamental concepts, starting from data preparation, to understanding types of algorithms, and their applications.
3. How to Learn Machine Learning — To Become a Data Scientist
If you are looking to pursue a career in Machine Learning, you cannot miss this article. It breaks down a step-by-step guide to learn Machine Learning, including resources, online courses, and certification.
4. Hands-on machine learning with Scikit Learn and TensorFlow
This article brings a practical approach to Machine Learning. You will learn to write code in both Scikit Learn and TensorFlow, which are Python libraries used to implement Machine Learning algorithms.
5. Understanding Confusion Matrix
The performance of a Machine Learning algorithm is measured using metrics such as Accuracy, Precision, Recall, and F1 Score. This article will help you understand these metrics and how to calculate them using the Confusion Matrix.
6. Machine Learning Applications You Should Know
Machine Learning is employed in various domains, such as Healthcare, Finance, Marketing, and more, to solve complex problems. This article lists several applications of Machine Learning in different industries and provides real-world examples.
7. Top 10 Machine Learning Libraries in Python
Python is the preferred choice for implementing Machine Learning algorithms. This article lists the top Machine Learning libraries in Python, including TensorFlow, Scikit-Learn, and Keras.
8. Neural Network Architecture: Understanding the Basics
Neural Networks are at the heart of Deep Learning, a subset of Machine Learning. This article breaks down the basics of Neural Network Architecture, including types of layers, activation functions, and optimization algorithms.
9. A Gentle Introduction to Gradient Boosting
Gradient Boosting is a popular method for building a predictive model. This article provides a gentle introduction to Gradient Boosting, including its inner workings and its advantages over other methods.
10. A Comprehensive Guide to Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are widely used in image recognition, speech recognition, and natural language processing applications. This article provides a comprehensive guide to CNNs, including the basics of convolution, types of layers, and applications.
Conclusion
Machine Learning is an exciting field with a plethora of applications. As a beginner, these 10 must-read articles will give you a solid foundation to start your journey. While these articles do not make you an expert overnight, they provide you with the necessary understanding of the fundamentals of Machine Learning, algorithms, applications, and tools to pursue further learning. Happy Learning!
