Overfitting Courses and Certifications

Association for Computing Machinery (ACM)

Does Learning Require Memorization? A Short Tale About a Long Tail

Explore the relationship between learning and memorization in machine learning, focusing on dataset fitting, interpolation, and long-tailed data distribution challenges.

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

Valerio Velardo - The Sound of AI

Solving Overfitting in Neural Networks

Learn techniques to identify and prevent overfitting in neural networks, including early stopping, audio data augmentation, dropout, and L1/L2 regularization, with practical implementation in a music genre classifier.

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

Richard McElreath

Statistical Rethinking 2022 - Overfitting

Explore overfitting in statistical modeling, covering cross-validation, regularization, information criteria, and robust regression techniques for improved predictive accuracy.

• YouTube
• 1 hour 12 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Overfitting: Benign, Tempered and Harmful - Lecture on Machine Learning Regularization

Explore the nuanced understanding of overfitting in neural networks, examining benign, tempered, and harmful effects on model performance based on data properties and training conditions.

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

Practical Machine Learning

27 reviews

Learn essential machine learning concepts and techniques, from data collection to model evaluation, with hands-on practice using popular algorithms and the caret package in R.

• Coursera
• 8-9 hours
• On-Demand
• Free Online Course (Audit)

fast.ai

Practical Deep Learning For Coders

7 reviews

Learn how to get a GPU server online suitable for deep learning— to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems.

• Independent
• 7 weeks, 10 hours a week
• On-Demand
• Free Online Course

Introduction to Deep Learning

Explore foundational deep learning theory and practice, covering key algorithms, architectures, and implementation in PyTorch. Develop skills to design and train neural networks for real-world applications.

• Udacity
• 4 weeks, 5-6 hours a week
• On-Demand
• Paid Course

Advanced Machine Learning Models for Prediction

Master advanced machine learning algorithms including SVM, decision trees, random forests, and neural networks for predictive modeling using Scikit-Learn, with focus on practical implementation and optimization.

• CodeSignal
• On-Demand
• Free Certificate

Modeling the Iris Dataset with TensorFlow

Master TensorFlow fundamentals through hands-on practice with the Iris dataset, covering data preprocessing, model building, performance evaluation, early stopping implementation, and model deployment techniques.

• CodeSignal
• On-Demand
• Free Certificate

Data Analytics Foundations for Accountancy II

10 ratings at Coursera

Explore machine learning concepts, algorithms, and practical applications in data analytics using Python. Gain skills in classification, regression, clustering, and anomaly detection for business insights.

• Coursera
• 2 days 22 hours 11 minutes
• On-Demand
• Free Online Course (Audit)

Introduction to Predictive Modeling

121 ratings at Coursera

Learn predictive modeling with linear regression and time series forecasting using Excel. Gain practical skills in data preparation, model fitting, interpretation, and forecasting for real-world decision-making.

• Coursera
• 12 hours 22 minutes
• On-Demand
• Free Online Course (Audit)

Population Health: Predictive Analytics

24 ratings at Coursera

Learn to develop and assess accurate prediction models for healthcare decision-making, covering study design, modeling techniques, and validation methods to improve preventive measures and individualized treatments.

• Coursera
• 22 hours 10 minutes
• On-Demand
• Free Online Course (Audit)

Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls

64 ratings at Coursera

Explore machine learning's technical aspects, from foundational principles to advanced methods. Learn to avoid pitfalls, interpret models, and evaluate performance while gaining insights into cutting-edge techniques and ethical considerations.

• Coursera
• 17 hours 26 minutes
• On-Demand
• Free Online Course (Audit)

Winning a Kaggle Competition in Python

Learn how to approach and win competitions on Kaggle.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Neural Networks and Random Forests

Explore advanced AI techniques: neural networks and random forests. Learn structure, coding, and applications. Complete projects on heart disease prediction and patient similarity analysis.

• Coursera
• 10 hours 16 minutes
• On-Demand
• Free Online Course (Audit)