Beginner Machine Learning Part 2

From Data to Insights: Your First Steps in Machine Learning as an AI technology

What you'll learn

Foundations of Machine Learning: Understand key concepts, types of machine learning, and the role of data in building intelligent systems.

Data Handling Skills: Learn essential data preprocessing techniques, including cleaning, normalization, and encoding for effective analysis.

Supervised & Unsupervised Learning: Explore regression, classification, and clustering methods, along with evaluation metrics for model performance.

Ethics & Applications: Gain insights into ethical considerations in AI, including bias, fairness, and responsible practices in machine learning development.

Requirements

Basic Programming Knowledge: Familiarity with programming concepts, preferably in Python, as it is commonly used in machine learning.

Description

Welcome to "Beginner Machine Learning Part 2"! If you have not taken Part 1 you should. So, are you curious about the transformative world of machine learning, you've come to the right place. This course is designed for absolute beginners, guiding you through the foundational concepts that power today's data-driven decisions.Why should you take this course? First, machine learning is revolutionizing industries, from healthcare to finance, and understanding its principles can open doors to exciting career opportunities. You'll learn the differences between traditional programming and machine learning, the critical role of data, and essential preprocessing techniques.We’ll explore exploratory data analysis, helping you visualize and interpret data effectively. Plus, you'll gain hands-on experience with supervised learning algorithms, including regression and classification, which are vital for making predictions and informed decisions.By the end of this course, you'll have a solid understanding of machine learning fundamentals, empowering you to tackle real-world challenges. Join us on this exciting journey and take your first step toward becoming a machine learning practitioner! Just remember that the world is driving to AI and it is a great great thing to be a part of that drive. AI is amazing, not scary, like everyone says. Machine Learning is a stellar way to jump into that world.

Overview

Section 1: Introduction

Lecture 1 Lecture 1: Advanced Classification Techniques

Lecture 2 Lecture 2: Unsupervised Learning

Lecture 3 Lecture 3: Dimensionality Reduction

Lecture 4 Lecture 4: Introduction to Neural Networks

Lecture 5 Lecture 5: Natural Language Processing (NLP)

Lecture 6 Lecture 6: Ethics in Machine Learning

Aspiring Data Scientists: Individuals looking to start a career in data science and gain foundational knowledge in machine learning.