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 how to fine-tune the current state-of-the-art EffecientNet V2 model to perform image classification on satellite data (EuroSAT) using TensorFlow in Python.
Learn how you can pretrain BERT and other transformers on the Masked Language Modeling (MLM) task on your custom dataset using Huggingface Transformers library in Python
Learn how to overcome imbalance related problems by either undersampling or oversampling the dataset using different types and variants of smote in addition to the use of the Imblearn library in Python.
Learn how to use Huggingface transformers library to generate conversational responses with the pretrained DialoGPT model in Python.
Learn how to use HuggingFace transformers library to fine tune BERT and other transformer models for text classification task in Python.
Learn how to use Huggingface transformers and PyTorch libraries to summarize long text, using pipeline API and T5 transformer model in Python.
Learn how to build a deep learning malaria detection model to classify cell images to either infected or not infected with Malaria Tensorflow 2 and Keras API in Python.
Learn how to handle stock prices in Python, understand the candles prices format (OHLC), plotting them using candlestick charts as well as learning to use many technical indicators using stockstats library in Python.