ML Maths Basics
Understand linear algebra, probability, and calculus concepts used in ML.
0%
Confidence · no data yet
After this skill you can…
- Manipulate vectors and matrices
- Understand gradient descent intuitively
- Apply Bayes' theorem and basic probability
Watch (10 videos)
ROC and AUC in R
→ Draw ROC curves in R→ Calculate AUC for model evaluation
Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python
→ Solve partial differential equations using numerical methods→ Implement numerical methods in Python
NumPy Crash Course - Complete Tutorial
→ Apply NumPy to scientific computing→ Use NumPy for data science tasks
L3.3 Vectorization in Python
→ Implement vectorization in Python→ Optimize machine learning models with NumPy
Naive Bayes from Scratch - Machine Learning Python
→ Implement Naive Bayes from scratch→ Understand Gaussian Naive Bayes
predict.m - Programming Assignment 2 Machine Learning
→ Implement predictive models in MATLAB→ Solve machine learning problems
Logistic Regression in Python - Machine Learning From Scratch 03 - Python Tutorial
→ Implement Logistic Regression in Python→ Use NumPy for ML algorithms
Machine Learning
→ Build machine learning models→ Deploy models using Python
Principal Component Analysis with NumPy
→ Implement Principal Component Analysis with NumPy→ Apply dimensionality reduction techniques
RStudio for Six Sigma - Hypothesis Testing
→ Conduct hypothesis testing with RStudio→ Identify data types for statistical analysis
DeepCamp AI