P — 01
Loading and Visualizing the MNIST Handwritten Digit Dataset
MNIST
Visualization
Data Loading
P — 02
Classification of MNIST Handwritten Digits
MNIST
ANN
Classification
P — 03
Binary Classification Model for Disease Risk Prediction using ANN
Binary Classification
ANN
Healthcare AI
P — 04
Image classification using CNN, 2 Convolutional layers on MNIST and CIFAR-10 dataset
CNN
MNIST
CIFAR-10
Conv Layers
P — 05
Handling and evaluating imbalance data using resampling, ensemble method and custom loss function
Handling dataset imbalance
Resampling
Ensemble
P — 06
Image Data Augmentation using Keras
Augmentation
Keras
Regularization
P — 07
ANN using Backpropagation with Different Activation Functions
Backpropagation
Activation Fn
ANN
P — 08
Deep Feedforward ANN with 4 Hidden Layers & Backpropagation
Deep ANN
4 Hidden Layers
Backpropagation
P — 09
Time Series Forecasting using Deep Learning with LSTM
LSTM
Time Series
Forecasting
P — 10
Image Data Comparison using Autoencoder Neural Network on CIFAR-10
Autoencoder
CIFAR-10
Reconstruction
P — 11
Deep CNN for Multiclass Image Classification — CPU vs GPU Performance
Deep CNN
GPU vs CPU
Multiclass
