/ML_TA_IIITB_2018

This repository contains TA sessions work for the Machine Learning course, Aug '18 - Dec '18.

Primary LanguageJupyter Notebook

ML_TA_IIITB_2018

This repository contains TA sessions work for the Machine Learning course, Aug '18 - Dec '18.

Requirements

  • Python3 : is an interpreted high-level programming language for general-purpose programming.

  • Numpy : is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

  • Pandas : is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.

  • Scipy : is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

  • Scikit-learn : is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

  • MatplotLib : is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications.

  • Seaborn : is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

  • openCV : is a library of programming functions mainly aimed at real-time computer vision. The library is cross-platform and free for use under the open-source BSD license. OpenCV supports the deep learning frameworks TensorFlow, Torch/PyTorch and Caffe.

  • PIL : adds image processing capabilities to your Python interpreter. This library supports many file formats, and provides powerful image processing and graphics capabilities.

Course Instructors

Teaching Assistants