A Deep-Learning Chess Engine with some awesome features
Machine Learning and Deep Learning lessons.
This repository is for contributing good quality study materials for learning TensorFlow for beginners from the basics to the intermediate or to an advanced level. Anyone can contribute your knowledge in this field, which can help the people who are interested in learning TensorFlow.
Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn.
COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning
Developed using Pybullet, OpenCV and Deep Learning
Earthquake Responses prediction using Deep learning and Database
A Deep Learning UCI-Chess Variant Engine written in C++ & Python