This repository contains the implementation of various Machine Learning Algorithms and Data Analysis techniques in Python.
- Basics - Contains the basic programs to get started with. It includes regression, classification, clustering, dimensionality reduction, etc from scratch.
- DA - Contains the programs related to Data Analysis like data cleaning, data visualization, etc.
- NLP - Contains the programs related to Natural Language Processing like Viterbi Algorithm, Hidden Markov Model, etc.
- Colabs - Contains the programs that are implemented in Google Colaboratory, mostly related to Deep Learning and Computer Vision. It includes Image Captioning, Denoising, Enhancements, etc.
- Minor - Contains the programs related to the Minor Project. It is a comparative study of various GAN models on the MNIST dataset.
- Test - Contains the programs for automation of data entry to Konnexions Society of KIIT.
- GAN - Contains the programs related to Generative Adversarial Networks optimising algos on non-convex loss functions.
- Proctoring-AI - Contains the programs related to Proctoring AI. It includes Face Recognition, Eye Tracking, etc.
- QuantumComp - An optimisation Algorithm for Quantum gate insertion in Quantum Circuits using genetic algorithm.
To run the programs in this repo, do the following:
- create a virtual environment using conda or venv.
conda create -n <env_name> python=3.7python -m venv <env_name>
- activate the virtual environment
conda activate <env_name>cd ./venv/Scripts/activate(windows users)source ./venv/bin/activate(mac and linux users)
- install the requirements
pip install --upgrade pip(to upgrade pip)pip install -r requirements.txt
Once the requirements have been installed, The programs will run successfully.
- Numpy - NumPy is the fundamental package for scientific computing with Python.
- Pandas - Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- Matplotlib - Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
- Seaborn - Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.
- Scikit-Learn - Scikit-learn is a free software machine learning library for the Python programming language.
- Tensorflow - TensorFlow is an end-to-end open source platform for machine learning.
- Keras - Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
- NLTK - NLTK is a leading platform for building Python programs to work with human language data.
- Spacy - Industrial-strength Natural Language Processing (NLP) with Python and Cython.
- hmmlearn - Hidden Markov Models in Python, with scikit-learn like API.
- OpenCV - OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library.
- Scikit-Image - Scikit-image is a collection of algorithms for image processing.
- Jupyter Notebook - Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
- Autograd - Autograd is a Python library that provides automatic differentiation for numpy code.
- Openpyxl - Openpyxl is a Python library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files.
- Keras Preprocessing - Keras Preprocessing is a collection of utilities for preprocessing data.
- PyAudio - PyAudio provides Python bindings for PortAudio, the cross-platform audio I/O library.
- SpeechRecognition - SpeechRecognition is a library for performing speech recognition, with support for several engines and APIs, online and offline.