PRACTICAL ML

ML hello world (Keras) (Numpy)
House price prediction (Keras on top of Tensorflow) (Numpy)
Fashion MNIST-1 (Multi class classifier) (IMAGES) (Tensorflow)
Fashion MNIST-2 (CallBacks)
MNIST (CNN) (Visualizing CONV and pool layers)
Cat vs Dog-1 (Binary class classfication) (ImageDataGenerator) (Understand Overfitting) (Working on your own data)
Cat vs Dog-2 (Data augmentation) (ImageDataGenerator) (Overfitting-Solution)
Cat vs Dog-visualization (tensorflow.keras.preprocessing.image)
Play with this (Try)
Horses vs Humans-Transfer learning (Transfer learning) (Inception-V3)

Building a model is a multi-stage process: -

Collect, clean and process data
Prototype and iterate on your model architecture
Train and evaluate results
Prepare your model for production

TO DO

Transfer learning (ResNets or inception_v3 or mobile net)
Transfer learning (with your own model)
Finding optimal learning rate (Using Callbacks)
Add cool real world projects (Pneumonia_detection, handwritten-mathematical-symbols, Face recognition, and much more)
Train model in browser (Javascript)
Convert and Deploy model (Website/browser (JS) and Android/IOS (Java) or Edge devices (Raspberry Pi)) (Static and dynamic) (using images and live camera feed) (Transfer learning)
Lambda layer
Working with Audio (NLP)
Sequences, Time Series and Prediction
Sequential models and Functional models

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Name		Name	Last commit message	Last commit date
Cat vs Dog-1.ipynb		Cat vs Dog-1.ipynb
Cat vs Dog-2.ipynb		Cat vs Dog-2.ipynb
Cat vs Dog-visualization.ipynb		Cat vs Dog-visualization.ipynb
Fashion_MNIST-1.ipynb		Fashion_MNIST-1.ipynb
Fashion_MNIST-2.ipynb		Fashion_MNIST-2.ipynb
Horses vs Humans-Transfer learning.ipynb		Horses vs Humans-Transfer learning.ipynb
House_price_pred.ipynb		House_price_pred.ipynb
LICENSE		LICENSE
ML hello world.ipynb		ML hello world.ipynb
MNIST.ipynb		MNIST.ipynb
Play with this.ipynb		Play with this.ipynb
README.md		README.md