InsidiousScare
Neural Networks Mock Exam: ReLU, CNN Dimensions, ResNet & Overfitting
24:20
InsidiousScare
How to Train Neural Networks Faster: Momentum, Dropout & Batch Norm
5:27
InsidiousScare
VGG vs ResNet Explained: Why Deeper Networks Failed (Until Now)
4:02
InsidiousScare
CNN Output Size Formula Explained: Convolution, Stride, and Padding
5:24
InsidiousScare
Backpropagation Explained: How Neural Networks Learn (Gradient Descent)
4:16
InsidiousScare
Deep Learning Intro: The Perceptron, ReLU Activation & The XOR Problem
4:03
InsidiousScare
Machine Learning Midterm Review: Practice Questions & Solutions
31:29
InsidiousScare
Why Accuracy is a Lie: Confusion Matrix, Recall & Precision Explained
6:16
InsidiousScare
Naive Bayes Classifier Explained: A Step-by-Step "Play Tennis" Example
7:08
InsidiousScare
k-Nearest Neighbors (k-NN) Explained: The Lazy Learner Algorithm
6:14
InsidiousScare
Principal Component Analysis (PCA): The 5 Steps & Eigenvalues Solved
9:26
InsidiousScare
Hierarchical Clustering Solved: Single Link vs Complete Link Calculation
5:58
InsidiousScare
How to Solve K-Means Iterations by Hand (Unsupervised Learning)
6:41
InsidiousScare
Machine Learning Exam Prep: Normalization, Jaccard vs SMC, and Distance Metrics
10:50