Regularization Courses and Certifications

Meaningful Predictive Modeling

49 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
• Paid Course

StatQuest with Josh Starmer

Regularization Part 1 - Ridge (L2) Regression

Learn Ridge Regression to prevent overfitting, solve unsolvable equations, and optimize models. Covers main ideas, details, applications for various data types and models, and usage with limited data.

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

AI skills for Engineers: Supervised Machine Learning

8 ratings at edX

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)

Coursera

Support Vector Machines in Python, From Start to Finish

162 ratings at Coursera

Build a Support Vector Machine classifier using scikit-learn and RBF Kernel to predict heart disease. Hands-on project using UCI Machine Learning Repository data, focusing on implementation and evaluation techniques.

• Coursera
• 1 hour 55 minutes
• On-Demand
• Paid Course

Modern Deep Convolutional Neural Networks with PyTorch

144 ratings at Udemy

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

• Udemy
• 1 hour 55 minutes
• On-Demand
• Free Online Course

Alexander Amini;  MIT

Introduction to Deep Learning

1 review

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques.

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

Practical AI and Machine Learning with Model Builder AutoML

50 ratings at Udemy

Master machine learning by doing it in practice, using an automated machine learning GUI that requires little/no coding.

• Udemy
• 3 hours 31 minutes
• On-Demand
• Paid Course

CertNexus

Build Regression, Classification, and Clustering Models

19 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
• Paid Course

Machine Learning Fundamentals

Discover supervised machine learning fundamentals, from linear regression to classification models, regularization techniques, and performance evaluation using ROC curves.

• Coursera
• 1 day 10 hours 7 minutes
• On-Demand
• Paid Course

Machine Learning with Neural Networks

Explore neural network fundamentals, backpropagation, regularization, and Bayesian methods for machine learning with hands-on TensorFlow implementation.

• Coursera
• 1 day 12 hours 52 minutes
• On-Demand
• Paid Course

Generative AI: Foundations and Concepts

Explore the mathematical foundations of generative AI, from neural networks to advanced deep learning models, with practical implementation techniques and applications in engineering.

• Coursera
• 21 hours 36 minutes
• On-Demand
• Paid Course

Machine Learning and Data Analytics Part 2

Explore advanced data mining techniques including clustering, neural networks, SVMs, and text mining with real-world applications across engineering sectors.

• Coursera
• 18 hours 7 minutes
• On-Demand
• Paid Course

Packt

Foundations of Model Optimization and Deep Learning

Master model optimization and CNNs through hyperparameter tuning, regularization techniques, and hands-on image classification projects using Keras, TensorFlow, and PyTorch.

• Coursera
• 7 hours 7 minutes
• On-Demand
• Paid Course

Master custom neural network design by comparing CNNs, RNNs, and Transformers, then build optimized PyTorch architectures with proper layers, activations, and regularization techniques.

• Coursera
• 1 hour 44 minutes
• On-Demand
• Paid Course

Packt

Applied Machine Learning and Model Optimization

Master advanced ML algorithms, hyperparameter tuning, and model optimization techniques through hands-on projects with XGBoost, ensemble methods, and real-world applications.

• Coursera
• 21 hours 9 minutes
• On-Demand
• Paid Course