Dive into a comprehensive lecture series covering fundamental machine learning concepts through an engaging and accessible approach. Learn about linear regression, support vector machines, principal component analysis, artificial neural networks, hierarchical clustering, Naïve Bayes classifiers, and association rule learning algorithms like Apriori and Eclat. Explore K-nearest neighbors, logistic regression, convolutional neural networks, and recurrent neural networks with LSTMs. Gain practical experience implementing these concepts using Keras and Python, providing a solid foundation for aspiring data scientists and machine learning enthusiasts.
Overview
Syllabus
Linear Regression - Fun and Easy Machine Learning.
Support Vector Machine (SVM) in 7 minutes - Fun Machine Learning.
Principal Component Analysis (Dimensionality Reduction) - Fun and Easy Machine Learning.
Fun and Easy Machine Learning Course in Keras and Python (Coupon Code in Description).
Artificial Neural Networks - Fun and Easy Machine Learning.
Hierarchical Clustering - Fun and Easy Machine Learning.
Naïve Bayes Classifier - Fun and Easy Machine Learning.
Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning.
Eclat Association Rule Learning - Fun and Easy Machine Learning Tutorial.
K - Nearest Neighbors - KNN Fun and Easy Machine Learning.
Logistic Regression - 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
