Repository containing portfolio of data science projects completed by me for academic, self learning, and hobby purposes. Presented in the form of iPython Notebooks, and Python files in corresponding modules .
| Library | Usage |
|---|---|
| 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. |
| Numpy | NumPy is a python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices. |
| Scikit Learn | Scikit-learn machine learning library for the Python programming language.[3] 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. |
| Statsmodel | Statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. |
| Scipy | 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 . |
| 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. |
| Tensorflow | TensorFlow is an end-to-end open source platform for machine learning and deep learning used to Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. |
| Keras | Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. |
| PyTorch | PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab. |
| Tensorflow.js | Develop ML models in JavaScript, and use ML directly in the browser. |
| OpenCV | OpenCV is a library of programming functions mainly aimed at real-time computer vision. |
