C

CourseWWWork

9 Followers
    49.2 Feature Transformation Using Sklearn With ANN Krish Naik ML
    24:42
    48.31 CNN Introduction Krish Naik ML
    8:06
    48.32 Human Brain Vs CNN Krish Naik ML
    7:23
    48.35 Padding In CNN Krish Naik ML
    5:51
    48.33 All you need to Know about Images Krish Naik ML
    6:37
    48.38 Flattening and Fully Connected Layers Krish Naik ML
    7:37
    48.36 Operation Of CNN Vs ANN Krish Naik ML
    7:33
    48.39 CNN example with RGB Krish Naik ML
    4:18
    48.37 Max, Min and Average Pooling Krish Naik ML
    10:06
    48.34 Convolution Operation In CNN Krish Naik ML
    15:46
    48.27 Adam Optimiser Krish Naik ML
    6:36
    48.28 Exploding Gradient Problem Krish Naik ML
    10:11
    48.30 Dropout Layers Krish Naik ML
    12:10
    48.29 Weight Initialisation Techniques Krish Naik ML
    11:57
    48.26 RMSPROP Krish Naik ML
    6:17
    48.2 Why Deep Learning is getting Popular Krish Naik ML
    12:45
    48.4 Advantages and Disadvantages of Perceptron Krish Naik ML
    6:50
    48.3 3 - Perception Intuition Krish Naik ML
    18:20
    48.9 Sigmoid Activation Function Krish Naik ML
    7:59
    48.7 Chain Rule of Derivatives Krish Naik ML
    11:03
    48.11 Tanh Activation Function Krish Naik ML
    6:54
    48.14 ELU Activation Function Krish Naik ML
    4:07
    48.13 Leaky Relu and Parametric Relu Krish Naik ML
    4:35
    48.5 ANN Intuition and Learning Krish Naik ML
    21:21
    48.10 Sigmoid Activation Function 2.0 Krish Naik ML
    13:49