Regularization Courses and Certifications

Richard McElreath

Statistical Rethinking 2023 - Fitting Over & Under

Explore advanced statistical concepts including cross-validation, regularization, and robust regression to enhance model fitting and selection techniques in data analysis.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Online Course

Simons Institute

Discrepancy Minimization via Regularization

Explore a novel algorithmic framework for discrepancy minimization, reinterpreting key breakthroughs and proving conjectures for pseudorandom instances through regularization techniques.

• YouTube
• 57 minutes
• On-Demand
• Free Online Course

Learn to improve machine learning model performance on new data using regularization techniques like ridge and lasso, minimizing overfitting and understanding the bias-variance tradeoff.

• Codecademy
• 2 hours
• On-Demand
• Free Trial Available

Data Science: Machine Learning

85 ratings at edX

Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

• edX
• 8 weeks, 2-4 hours a week
• On-Demand
• Free Online Course (Audit)

Meaningful Predictive Modeling

47 ratings at Coursera

Evaluate and compare predictive models using diagnostic techniques and performance measures. Learn to implement training/validation/test pipelines for robust model generalization.

• Coursera
• 8 hours 33 minutes
• On-Demand
• Free Online Course (Audit)

DeepLearning.AI;  Stanford

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

63066 ratings at Coursera

Enhance deep learning skills: master hyperparameter tuning, regularization, optimization, and TensorFlow implementation for improved neural network performance and systematic results generation.

• Coursera
• 23 hours 35 minutes
• On-Demand
• Free Online Course (Audit)

AI skills for Engineers: Supervised Machine Learning

Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems using the Python toolbox scikit-learn.

• edX
• 6 weeks, 6-8 hours a week
• On-Demand
• Free Online Course (Audit)

DeepLearning.AI;  Stanford

Supervised Machine Learning: Regression and Classification

22118 ratings at Coursera

Develop machine learning skills using Python, covering regression and classification techniques with hands-on practice in NumPy and scikit-learn for real-world AI applications.

• Coursera
• 1 day 9 hours 19 minutes
• On-Demand
• Free Online Course (Audit)

A deep understanding of deep learning (with Python intro)

4322 ratings at Udemy

Master deep learning in PyTorch using an experimental scientific approach, with lots of examples and practice problems.

• Udemy
• 2 days 9 hours 20 minutes
• On-Demand
• Paid Course

Master Machine Learning , Deep Learning with Python

120 ratings at Udemy

Complete course covering fundamentals of Machine learning , Deep learning with Python code

• Udemy
• 5 hours
• On-Demand
• Paid Course

Modern Deep Convolutional Neural Networks with PyTorch

98 ratings at Udemy

Image Recognition with Convolutional Neural Networks. Advanced techniques for Deep Learning and Representation learning

• Udemy
• 1-2 hours
• On-Demand
• Free Online Course

Simplified: Intro to Machine Learning

49 ratings at Udemy

Learn what machine learning is all about in this beginner-level entry course

• Udemy
• 1-2 hours
• On-Demand
• Paid Course

CertNexus

Build Regression, Classification, and Clustering Models

14 ratings at Coursera

Learn to build regression, classification, and clustering models using various algorithms. Gain hands-on experience in model selection, evaluation, and tuning for supervised and unsupervised learning tasks.

• Coursera
• 20 hours 19 minutes
• On-Demand
• Free Online Course (Audit)

Data Analysis and Visualization

This course will introduce students to the field by covering state­-of-­the-art modeling, analysis and visualization techniques.

• Udacity
• 16 weeks
• On-Demand
• Free Online Course

Machine Learning Course

1 review

Comprehensive exploration of machine learning fundamentals, covering linear models, neural networks, SVMs, and key principles for effective algorithm implementation and evaluation.

• YouTube
• 1 day
• On-Demand
• Free Online Course