Home
Documentation
Courses
root
5
How to Read a Paper
Languages
1
Python
1
poetry
Linux
1
SLURM
Machine Learning
1
Deep Learning
1
Novice
2
Module 1 - Lesson 1: Linear Classifiers and Gradient Descent
13
Components of A Parametric Learning Algorithm
DL Book Linear Algebra
DL Book Machine Learning Basics
DL Book Probability And Information Theory
Deep Learning
Gradient Descent
How is Deep Learning Different: DR
How is Deep Learning Different: End-to-End
How is Deep Learning Different: HC
Linear Algebra View: Vector and Matrix Sizes
Performance Measure For A Classifier
Supervised Learning and Parametric Models
The Bandwagon
introduction
Mathematics
2
Calculus
3
Partial Derivatives
derivatives
partial derivatives
Linear Algebra
1
matrix multiplication
Documentation
Under Construction
Total Documentation Progress:
40%
Basic Documentation:
80%
Search:
0%
Random Bug Fixes:
0%
Select Theme
Dark
Dark (Colorblind)
Light
Light (Colorblind)
Close Theme Menu
Home
Docs
Board
HuggingFace
Docker Hub
PyTorch
TensorFlow
JAX
NumPy
Pandas
Unify
Ray
Ultralytics
Polars
Jupyter
Google Colab
Paperspace
LangChain
Milvus