Machine-Learning

This repo contains all the materials I create during my ML learning journey. :)

Basic Programming

1. Numpy
   • Different ways of creating numpy arrays: np.array, np.zeros, np.ones, np.random.random, np.random.randint, etc.
   • Array attributes: .shape, .ndim, .itemsize, .size, .dtype, .nbytes
   • Reshaping and slicing
   • Joining arrays: np.vstack, np.hstack, np.dstack, and np.concatenate
   • Splitting arrays: np.vsplit, np.hsplit, np.dsplit, np.split
   • NumPy ufuncs
   • Aggregations: min, max, sum, median etc.
   • Broadcasting, masking and sorting using sort, argsort, partition and argpartition and their use cases.
2. Pandas

   • Pandas objects: Series, DataFrame and Index

   • Data indexing and selection: slicing and masking

   • Operations on data: Ufuncs

   • Handling missing data: None of Python and Nan of numpy

   • Operations on null vaues: isnull, notnull, dropna, fillna

   • Joining dataframes: concat and merge

   • Aggregations and Groupby

     Vectorized string operations and time series data handling can be covered from Pandas official documentation.

3. Matplotlib

Time Series Forecasting

Notebooks on time series forecasting.

Problems

Python solutions to Project Euler problems.