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Experiments with some of the basic algorithms in AI using Python and other frameworks such Tensorflow and Keras:
Genetic Algorithm
Bayesian Classifier for Text Classification
Understanding of some of the popular optimizers used in Deep Learning.
Working with Word Embeddings.
Experimentation with various approaches in developing Convolutional Neural Networks for Image Classification like using Dropout, Batch Normalization and Transfer Learning to acheive high accuracy.
The .ipynb files were developed in Google Colab (You can use that for ease of implementation)