YOLO-V5: Segmentation & Classification || YOLO OBJECT DETECTION SERIES

YOLO-V5: Architecture deep-dive || YOLO OBJECT DETECTION SERIES

Generative AI: Evolution of Architectures of ChatGPT, Gemini etc

Generative AI: Transformers Architecture

YOLO-V4: Data Augmentation & Training strategies || YOLO OBJECT DETECTION SERIES

Generative AI: NLP Foundation Models

Generative AI: Introduction to Gen AI & Applications

YOLO-V4: MiWRC, CmBN, DROP BLOCK, CIOU, DIOU || YOLO OBJECT DETECTION SERIES

Batch Normalization - Part 4: Python Implementation on MNIST dataset

Batch Normalization - Part 3: Backpropagation & Inference

Batch Normalization - Part 2: How it works & Essence of Beta & Gamma

Batch Normalization - Part 1: Why BN, Internal Covariate Shift, BN Intro

Neural Networks From Scratch - Lec 24 - Regression Losses - Mean Square Logarithmic Error

YOLO-V4: CSPDARKNET, SPP, FPN, PANET, SAM || YOLO OBJECT DETECTION SERIES

YOLO-V4: Optimal Speed & Accuracy || YOLO OBJECT DETECTION SERIES

YOLO-V3: An Incremental Improvement || YOLO OBJECT DETECTION SERIES

YOLO-9000 - An Object Detector for 9000 classes || YOLO OBJECT DETECTION SERIES

YOLO V2 - Better, Faster & Stronger || YOLO OBJECT DETECTION SERIES || YOLO9000

YOLO V1 - YOU ONLY LOOK ONCE || YOLO OBJECT DETECTION SERIES

Neural Networks From Scratch - Lec 23 - Regression Losses - Smooth L1 Loss and Huber Loss Functions

Remove the confusion once for all! Cost Function vs Loss Function vs Objective Function

Neural Networks From Scratch - Lec 22 - MAE vs RMSE, Comparison with an Example

What is Numpy? Why Numpy arrays are faster than python lists?

MNIST Classification: Hands-on Project in PyTorch 1.12

PyTorch Vs Tensorflow: Jobs, Research and Industries. Who is the winner in 2022?

MNIST Classification: Hands-on Project in Tensorflow 2.8

Building a Neural Network from scratch: MNIST Project (No Tensorflow/Pytorch, Just Numpy)

Neural Networks From Scratch - Lec 21 - Regression Losses - MSE & RMSE

Neural Networks From Scratch - Lec 20 - Regression Losses - MAE, MAPE & MBE

Neural Networks From Scratch - Lec 19 - Approaching Regression Problem with Neural Networks

Neural Networks From Scratch - Lec 18 - Typical Neural Network Training Setup

Neural Networks From Scratch - Lec 17 - Python Implementations of all Activation functions

Neural Networks From Scratch - Lec 16 - Summary of all Activation functions in 10 mins

Neural Networks From Scratch - Lec 15 - GeLU Activation Function

Neural Networks From Scratch - Lec 14 - Mish Activation Function

Neural Networks From Scratch - Lec 13 - Swish Activation Function

Neural Networks From Scratch - Lec 12 - Softplus Activation Function

Neural Networks From Scratch - Lec 11 - Maxout Activation Function

Neural Networks From Scratch - Lec 10 - ReLU & Its Variants

Neural Networks From Scratch - Lec 9 - ReLU Activation Function

Neural Networks From Scratch - Lec 8 - Softmax Activation Function

Neural Networks From Scratch - Lec 7 - Tanh Activation Function

Neural Networks From Scratch - Lec 6 - Sigmoid Activation Function

Neural Networks From Scratch - Lec 5 - Step Activation Function

Neural Networks From Scratch - Lec 4 - Why Activation Functions and Properties they should have

Neural Networks From Scratch - Lec 3 - An Intuition on Neural Networks

Neural Networks From Scratch - Lec 2 - Coding a Neural Network in Python

Neural Networks From Scratch - Lec 1 - Introduction & coding a Neuron

Neural Networks From Scratch - Course Intro and Curriculum