Learn how to build machine learning and deep learning models for many purposes in Python using popular frameworks such as TensorFlow, PyTorch, Keras and OpenCV.
Learn what is transfer learning and how to use pre trained MobileNet model for better performance to classify flowers using TensorFlow in Python.
Building a deep learning model to generate human readable text using Recurrent Neural Networks (RNNs) and LSTM with TensorFlow and Keras frameworks in Python.
Building and training a model that classifies CIFAR-10 dataset images that were loaded using Tensorflow Datasets which consists of airplanes, dogs, cats and other 7 objects using Tensorflow 2 and Keras libraries in Python.
Classifying emails (spam or not spam) with GloVe embedding vectors and RNN/LSTM units using Keras and TensorFlow in Python.
Building a Speech Emotion Recognition system that detects emotion from human speech tone using Scikit-learn library in Python