This course aims to provide a fun and easy introduction to Machine Learning in Python and Keras. The learning outcomes include implementing common machine learning algorithms on real data, gaining exposure to neural networks and deep learning algorithms, and applying Python-based data science techniques. The course teaches regression, classification, clustering, association rule learning, dimensionality reduction, and neural networks. The teaching method involves whiteboard explanations, practical Python labs, and hands-on implementation of techniques on real data. The course is designed for beginners interested in Machine Learning without complex math, offering a practical approach to learning state-of-the-art concepts in a simple and engaging manner.
Overview
Syllabus
Fun and Easy Machine Learning Course in Keras and Python (Coupon Code in Description).
Linear Regression - Fun and Easy Machine Learning.
Logistic Regression - Fun and Easy Machine Learning.
K - Nearest Neighbors - KNN Fun and Easy Machine Learning.
Support Vector Machine (SVM) in 7 minutes - Fun Machine Learning.
Naïve Bayes Classifier - Fun and Easy Machine Learning.
Hierarchical Clustering - Fun and Easy Machine Learning.
Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning.
Eclat Association Rule Learning - Fun and Easy Machine Learning Tutorial.
Artificial Neural Networks - Fun and Easy Machine Learning.
Convolutional Neural Networks - Fun and Easy Machine Learning.
Recurrent Neural Networks LSTMs and Vanishing & Exploding Gradients - Fun and Easy Machine Learning.
Taught by
Augmented Startups
