Machine Learning Courses and Certifications

Traversy Media

Machine Learning Crash Course With ML.NET

Comprehensive introduction to machine learning concepts and hands-on demonstration using ML.NET, covering key processes from data loading to model evaluation with practical C# examples.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Association for Computing Machinery (ACM)

Designing an ML Minded Product and a Product Minded ML System

Explore designing ML-minded products and product-minded ML systems, focusing on data considerations, bias removal, evaluation methods, and sustainable implementation in real-world applications.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Krish Naik

End to End ML Project With Deployment - Project Problem Statement, EDA and Model Training

Comprehensive guide to building and deploying a machine learning project, covering problem definition, exploratory data analysis, feature engineering, and model training.

• YouTube
• 39 minutes
• On-Demand
• Free Video

Hackaday

TinyML - Using Machine Learning on Microcontrollers to Recognize Speech

Learn to implement speech recognition on microcontrollers using TinyML. Train a neural network, convert it to TensorFlow Lite, and deploy it on an ARM board for real-time wake word detection.

• YouTube
• 1 hour 59 minutes
• On-Demand
• Free Video

Valerio Velardo - The Sound of AI

Preprocessing Audio Datasets for Machine Learning

Build an audio preprocessing pipeline for AI in Python, covering STFT, zero-padding, and min-max normalization. Learn to batch process audio files efficiently for machine learning applications.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Alfredo Canziani

PCA, AE, K-Means, Gaussian Mixture Model, Sparse Coding, and Intuitive VAE

Explore advanced machine learning techniques including PCA, autoencoders, K-means, Gaussian mixture models, sparse coding, and VAEs. Gain insights into their applications and intuitive interpretations.

• YouTube
• 1 hour 54 minutes
• On-Demand
• Free Video

Alfredo Canziani

Supervised and Self-Supervised Transfer Learning With PyTorch Lightning

Explore supervised and self-supervised transfer learning techniques using PyTorch Lightning, comparing their implementation, training, and generalization capabilities in deep learning applications.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Simons Institute

Generalization Bounds for Neural Network Based Decoders

Explore generalization bounds for neural network decoders, examining their implications for information-theoretic approaches in trustworthy machine learning.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Simons Institute

Optimal Neural Network Compressors and the Manifold Hypothesis

Explore the intersection of neural network compression and the manifold hypothesis, examining optimal compressors and their implications for machine learning efficiency and performance.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Simons Institute

Fairness Without Imputation: A Decision Tree Approach for Fair Prediction With Missing Values

Explore a novel decision tree approach for fair prediction with missing data, addressing fairness concerns without relying on imputation techniques.

• YouTube
• 35 minutes
• On-Demand
• Free Video

Simons Institute

Improving Accuracy-Privacy Tradeoff via Model Reprogramming

Explore innovative techniques for enhancing the balance between model accuracy and data privacy through advanced model reprogramming strategies.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Fields Institute

Machine Learning for Prediction of Terrestrial Climate and Weather

Explore cutting-edge applications of machine learning in predicting terrestrial climate and weather patterns, presented by a leading expert from the University of Maryland.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Fields Institute

The Evolution of Natural Language Processing - Advice and Responsible Investing

Explore NLP's evolution, its impact on AI advisors, and ethical considerations in responsible investing through cutting-edge language models and representation learning.

• YouTube
• 39 minutes
• On-Demand
• Free Video

Fields Institute

JAX- Accelerated Machine Learning Research via Composable Function Transformations in Python

Explore accelerated machine learning research using JAX, a Python library for composable function transformations, enhancing ML model development and experimentation.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Fields Institute

Dual Principal Component Pursuit

Explore a novel approach to learning subspaces from corrupted data, tolerating high outlier ratios and dimensions. Discover algorithms and theoretical guarantees for this non-convex optimization problem.

• YouTube
• 51 minutes
• On-Demand
• Free Video