Machine Learning Tutorials

Explore different pre-trained transformer models in transformers library to paraphrase sentences in Python.

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 generate any type of text with GPT-2 and GPT-J transformer models with the help of Huggingface transformers library in Python.

Learn how to perform speech recognition using wav2vec2 and whisper transformer models with the help of Huggingface transformers library in Python.

Learn how to use Huggingface transformer models to perform machine translation on various languages using transformers and PyTorch libraries 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 perform age and gender detection using OpenCV library in Python with camera or image input.

Learn how to perform gender detection on detected faces in images using OpenCV library in Python.

Learn how to predict someone's age from his front face picture using OpenCV 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 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.