Regularization Courses and Certifications

UofU Data Science

Nonlinear Regression and Regularization in Data Mining - Spring 2023

Master nonlinear regression concepts, from polynomial mappings to regularization techniques, while learning practical implementation in Python and understanding cross-validation for model optimization.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

ACM SIGPLAN

Fast Client-Driven CFL-Reachability via Regularization-Based Graph Simplification

Discover MoYe, a regularization-based graph simplification technique that accelerates CFL-reachability analysis by pruning non-contributing edges for targeted optimization.

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

Data Science: Building Machine Learning Models

120 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)

Microcredential

Comprehensive Introduction to Tensorflow

21 ratings at CodeSignal

Master TensorFlow fundamentals through hands-on practice, from basic tensor operations to advanced neural networks, model optimization, and deployment techniques for building efficient deep learning solutions.

• CodeSignal
• 12 hours
• On-Demand
• Free Certificate
• 4 courses

Intro to Model Optimization in Machine Learning

Master machine learning optimization techniques using real medical data, from hyperparameter tuning to advanced ensemble methods, enhancing your ability to build accurate predictive models.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Diving Deep into Regression

Master advanced regression techniques from polynomial to elastic net, with hands-on practice using real datasets for predictive modeling and performance optimization.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

PyTorch Techniques for Model Optimization

Master advanced PyTorch optimization techniques including regularization, dropout, batch normalization, and learning rate scheduling to enhance model performance and prevent overfitting.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Model Evaluation and Optimization

Master advanced techniques for evaluating and optimizing regression models, from cross-validation to hyperparameter tuning and regularization methods for enhanced predictive accuracy.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

TensorFlow Techniques for Model Optimization

Master advanced TensorFlow optimization techniques, from regularization and dropout implementation to callback utilization and Scikit-Learn integration, enhancing model performance and preventing overfitting.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Microcredential

Improving Machine Learning and Deep Learning Models

Master model optimization through hands-on techniques covering evaluation, regularization, hyperparameter tuning, and neural network enhancement with scikit-learn, XGBoost, and PyTorch.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate
• 4 courses

PredictHealth's Advanced Pricing System

Master advanced modeling techniques to build state-of-the-art insurance pricing systems with non-linear patterns, feature interactions, regularization, and robust validation methods.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Time Series Forecasting with LSTMs

1 review

Master LSTM networks for time series forecasting with PyTorch, building optimized models that handle long-term dependencies and evaluating performance using RMSE, MAE, and MAPE metrics.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

A deep understanding of deep learning (with Python intro)

6185 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 19 minutes
• On-Demand
• Paid Course

Microcredential

Foundations of Neural Networks

20 ratings at Coursera

Master advanced neural network concepts, from foundational theory to practical implementation in Python, while exploring ethical considerations in AI system development.

• Coursera
• 12 weeks, 4 hours a week
• On-Demand
• Paid Course
• 3 courses

Introduction to Neural Networks

Master foundational concepts of neural networks, from basic mathematics to advanced architectures like CNNs. Build practical skills in deep learning, optimization techniques, and model training through hands-on experience.

• Coursera
• 18 hours 20 minutes
• On-Demand
• Paid Course