Data Science: Supervised Machine Learning in Python from Udemy

Overview

AI and machine learning have been making huge strides in recent years, impacting a wide variety of industries such as finance, medicine, and robotics. This online course delves into essential machine learning algorithms to provide you with a deep and practical understanding of their concepts and implementations. The course covers K-Nearest Neighbor, Naive Bayes Classifier, Decision Trees, and Perceptron algorithms, all of which will be implemented from scratch.

Rather than just learning to use an API, this course focuses on helping you truly comprehend how machine learning models work, teaching you to visualize what’s happening internally. By the end of the course, you’ll also have a solid understanding of more practical aspects of machine learning, like hyperparameters, cross-validation, feature extraction, and feature selection. Finally, you’ll cap off your learning experience with the creation of a web service that runs a machine learning model and makes predictions, a real-world and practical application. The course materials are all free, and the prerequisites include knowledge of calculus, probability, Python coding, and experience with Numpy, Scipy, and Matplotlib.

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Skills you’ll learn

1. Understanding and implementing K-Nearest Neighbor algorithm
2. Mastering Naive Bayes and General Bayes Classifier
3. Implementing Decision Tree algorithm
4. Learning about Perceptrons and their connection to neural networks and deep learning
5. Practical machine learning concepts: hyperparameters, cross-validation, feature extraction, feature selection, and multiclass classification
6. Comparing machine learning with deep learning
7. Using Sci-Kit Learn library for efficient, optimized code
8. Creating a web service that runs a machine learning model and makes predictions

Summary

Delve into the intriguing realm of Data Science with the highly-rated course “Supervised Machine Learning in Python,” masterfully instructed by the proficient Lazy Programmer Team. Consisting of 55 engaging lessons, this course has captivated the minds of over 20,779 eager students, securing an impressive 4.7 out of 5-star rating. Don’t miss out on this remarkable opportunity to enhance your Python skills and knowledge!