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 use Huggingface transformers library to generate conversational responses with the pretrained DialoGPT model in Python.
Learn how to use Scikit-Learn library in Python to perform feature selection with SelectKBest, random forest algorithm and recursive feature elimination (RFE).
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 use the visualization tool Plotly to implement and create dynamic plots and figures (such as scatters, histograms, and candlesticks) 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.
Learn how to use transfer learning to build a model that is able to classify benign and malignant (melanoma) skin diseases in Python using TensorFlow 2.
Learn how to build a deep learning model that is able to detect and recognize your gender just by your voice tone using Tensorflow framework in Python.
Blurring and anonymizing faces in images and videos after performing face detection using OpenCV library in Python.
