Bias-Variance Tradeoff Courses and Certifications

Machine Learning Essentials

Explore statistical learning techniques for machine learning, including linear regression and classification. Apply concepts through Python coding assignments and practical problem-solving.

• Coursera
• 17 hours 59 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)

Model Validation in Python

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

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

Practicing Statistics Interview Questions in Python

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

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

Machine Learning Guide: Learn Machine Learning Algorithms

204 ratings at Udemy

Machine Learning: A comprehensive guide to machine learning. Learn machine learning algorithms & machine learning tools

• Udemy
• 1 hour 7 minutes
• On-Demand
• Paid Course

Statistical Learning

Explore cutting-edge statistical analysis techniques, from regression to advanced methods like kernel smoothing and support vector machines. Enhance data interpretation skills with hands-on Python examples.

• Coursera
• 4 days 19 hours 15 minutes
• On-Demand
• Free Online Course (Audit)

Machine Learning with Tree-Based Models in Python

48 ratings at DataCamp

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

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

Machine Learning Course

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 Video

NPTEL;  IIT Ropar

Deep Learning

In this course, we will learn about the building blocks used in these Deep Learning based solutions. Specifically, we will learn about feedforward neural networks, convolutional neural networks, recurrent neural networks and attention mechanisms.

• YouTube
• 1 day 3 hours
• On-Demand
• Free Video

Learning To See

In this series, we'll explore the complex landscape of machine learning and artificial intelligence through one example from the field of computer vision: using a decision tree to count the number of fingers in an image. It's gonna be crazy.

• YouTube
• 2 hours 30 minutes
• On-Demand
• Free Video

The Information Knot - Tying Sensing and Action; Emergence Theory of Representation Learning

Explore information theory, representation learning, and AI concepts with NYU's Stefano Soatto. Delve into information bottlenecks, mutual information, and disentangling in this advanced seminar on modern AI.

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

University of Tübingen

Introduction to Machine Learning

Explore key machine learning concepts and techniques, from linear regression to deep learning, clustering, and dimensionality reduction, with hands-on applications.

• YouTube
• 11 hours
• On-Demand
• Free Online Course

Advanced Predictive Modeling: Mastering Ensembles and Metamodeling

80 ratings at LinkedIn Learning

Learn how to use ensembles and metamodeling to create more accurate predictive models.

• LinkedIn Learning
• 1 hour 11 minutes
• On-Demand
• Free Trial Available

Chennai Mathematical Institute;  NPTEL

Predictive Analytics - Regression and Classification

Explore statistical predictive models for data science, covering regression, classification, and advanced techniques. Gain practical skills in model construction, implementation, and analysis using various programming languages.

• Swayam
• 12 weeks
• 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