Maths
Mathematics for AI & ML
Course
AI & ML Course Overview
less than a minute
What to expect from this AI & ML course?
Maths for AI & ML
This sheet contains all the topics that will be covered for Maths for AI & ML.
Below is the list of topics that will be covered in this course.
- Probability
- Statistics
- Linear Algebra
- Calculus
- Co-Ordinate Geometry (used everywhere for visualizing graphs of line, curve, plane, etc.)
We will understand each topic from pure AI & ML perspective.
We will NOT go into much of theoretical proof of everything.
However, we will dive deep as and when required.
However, we will dive deep as and when required.
Classical Machine Learning
Supervised Learning
- Linear Regression
- Logistic Regression
- K Nearest Neighbours
- Decision Trees
- Support Vector Machines
Unsupervised Learning
- K Means Clustering
- Hierarchical Clustering
- DBSCAN
- Gaussian Mixture Modeling
- Anomaly Detection
- t-SNE
- UMAP
Recommendation Systems
- Content Based Filtering
- Collaborative Filtering
- Matrix Factorization
- Non-Negative Matrix Factorization
- Alternating Least Squares
- Netflix Prize
- Market Basket Analysis
- Apriori Algorithm
- Association Rule Mining
Time Series Analysis
- Auto Correlation Function
- Auto Regressive Modeling
- Moving Average
- ARIMA
- SARIMA
- SARIMAX
Deep Learning
- Neural Networks
- Computer Vision
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
- Natural Language Processing
- Text Representation
- Language Modeling
- Word Embeddings
- Recurrent Neural Networks
- Long Short Term Memory Networks
- Attention Mechanism
- Self Attention
- Transformers
- BERT
- GPT-2