Data structure problems and exercises.

This repository contain detailed concepts for Graphs and trees. There are some coding problems which were solved in an optimal way to get better time and space complexity.These would help in faster data processing and better memory management,

The repository provides implementations for

Project Structure

• DSA basics/ LRU cache, trees, sorting and searching algorithms.

• LinkedList/ Linked list problems such as reversing linked list, mergining multiple LL.

• Recursion/ Recursion and backtracking.

• Trees/ Problems to understand binary tree.

• backup/ Some scripts which I wrote in jupyterhub which has some of the coding problems and concepts.

• Coding Problems/ All the problems which were solved by mee from leetcode.

• Machine Learning/ Some concepts about machine learning such as regression, classification, clustering algorithms and accuracy estimation of each model.

Python Compatibility

The content in this collection supports Python 3.6 and higher

Installation

git clone https://github.com/IBM/Python-Graph-MachineLearning.git

You might need Anaconda navigator for some of the scripts.

Installing Navigator Navigator is automatically installed when you install Anaconda Distribution version 4.0.0 or higher.

If you have Miniconda or a version of Anaconda Distribution older than 4.0.0 installed, install Navigator from Anaconda Prompt, Terminal, or other command line interface by running the command conda install anaconda-navigator.

For more information on using Navigator, see https://docs.anaconda.com/anaconda/install/index.html

License

All source files must include a Copyright and License header.

#
# (c) Copyright contributors to the Python-Graph-MachineLearning project
#

This project is licensed under the Apache License 2.0. Click here to obtain a copy of the License.

It is a permissive license whose main conditions require preservation of copyright and license notices. Contributors provide an express grant of patent rights. Licensed works, modifications, and larger works may be distributed under different terms and without source code.

The examples are provided for tutorial purposes only. A complete handling of error conditions has not been shown or attempted, and the programs have not been submitted to formal IBM testing. The programs are distributed on an 'AS IS' basis without any warranties either expressed or implied.

If you would like to see the detailed LICENSE click here.