43:37

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

15:55

Batch Normalization - Part 4: Python Implementation on MNIST dataset

27:19

Batch Normalization - Part 3: Backpropagation & Inference

24:58

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

38:24

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

26:45

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

52:52

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

20:33

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

29:38

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

14:33

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

39:07

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

35:25

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

10:13

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

05:56

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

12:51

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

21:30

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

36:51

MNIST Classification: Hands-on Project in PyTorch 1.12

14:38

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

23:48

MNIST Classification: Hands-on Project in Tensorflow 2.8

34:15

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

05:22

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

06:49

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

05:41

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

11:23

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

09:16

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

12:56

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

08:45

Neural Networks From Scratch - Lec 15 - GeLU Activation Function

05:50

Neural Networks From Scratch - Lec 14 - Mish Activation Function

09:11

Neural Networks From Scratch - Lec 13 - Swish Activation Function

03:33

Neural Networks From Scratch - Lec 12 - Softplus Activation Function

08:34

Neural Networks From Scratch - Lec 11 - Maxout Activation Function

06:06

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

09:34

Neural Networks From Scratch - Lec 9 - ReLU Activation Function

07:50

Neural Networks From Scratch - Lec 8 - Softmax Activation Function

09:02

Neural Networks From Scratch - Lec 7 - Tanh Activation Function

13:05

Neural Networks From Scratch - Lec 6 - Sigmoid Activation Function

07:21

Neural Networks From Scratch - Lec 5 - Step Activation Function

11:16

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

10:39

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

17:07

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

16:38

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

02:44

Neural Networks From Scratch - Course Intro and Curriculum