Starting My 100 Days Machine Learning Journey

Today marks the beginning of my 100-day Machine Learning (ML) journey, where I will be diving deep into the world of Artificial Intelligence (AI). My goal is to master the essential concepts, techniques, and tools that make up the foundation of AI, covering everything from Python programming to advanced deep learning techniques. I’m excited to document this journey and share insights that will be valuable for both beginners and advanced learners.

This roadmap will be my guide, and throughout this series of articles, I’ll explore each topic step by step, ensuring a strong understanding of the key concepts. Here’s a sneak peek into what I’ll be covering in this series.

1. Python Programming

Python is the heart of machine learning and AI development. I’ll start by ensuring a solid foundation in Python programming before diving into more complex topics.

2. Data Analysis

Data is the foundation of machine learning. During this phase, I will focus on two of the most powerful Python libraries for data analysis:

• Numpy
• Pandas

3. Data Visualization

Visualizing data is critical to understanding the relationships and patterns within it. I’ll use:

• Matplotlib
• Seaborn

4. Statistics

Statistics is the backbone of machine learning. I will cover the essential concepts of:

• Probability Distributions
• Hypothesis Testing
• Regression Analysis

5. Machine Learning

This is where the core machine learning algorithms come into play. I’ll learn:

• Supervised Learning
• Unsupervised Learning
• Predictive Analytics

The ultimate goal here is to develop a strong understanding of both theory and practical implementation of machine learning algorithms.

6. Natural Language Processing (NLP)

NLP is an exciting branch of AI that focuses on understanding and manipulating human language. I’ll dive into:

• Text Processing
• Advanced Techniques
• Language Models

7. Deep Learning

Deep learning is the frontier of AI research, and I’ll explore:

• Neural Networks
• Popular Frameworks
• CNNs and RNNs

8. Computer Vision

Finally, I’ll touch on computer vision, another fascinating domain of AI:

• OpenCV
• Neural Networks for Vision
• Image Analysis