edualgo / grokking-machine-learning

This repo aims to contain different machine learning use cases along with the descriptions to the model architectures

       

Objective

A python package published at PyPi. The project can be viewed here => PyPi - eduAlgo. Don't forget to create an ISSUE before making a PR and always make PR to this repo - Main eduAlgo

Stats

Aim Of The Package

This is a very simple python package made up with python script to study different algorithms for educational purposes. This package is currently under planning version and aims to achieve the following :-

• To put together all the available algorithms
• Help students with learning space and time complexity
• Visualizing Algorithms
• Getting resources, articles etc. to study about python and Algorithms
• Become a handy tool for the programmers while using different algorithms on daily basis

Organization

This project is a part of the organization Edualgo Academy.

We are an opensource organization having a few open-sourced projects on github related to Data structures and Algorithms in Python, Flutter Development & Frontend Development. chek the organization here - eduAlgo

Documentation

The documentation for the included methods and their implementations can be found here => eduAlgo-Documentation

Algorithms Yet to Publish

• Searching Algorithms and Visualizations
• Sorting Algorithms and Visualizations
• Graph Algorithms and Visualizations
• Linked List Implementations and Vizualizations
• Tree Types, Vizualizations and Implementations

Installation

Fast install:

pip install eduAlgo

Example

from edualgo import LinkedList as ll
llist1 = ll.linkedlist()
llist2 = ll.linkedlist()

arr1 = list(map(int,input().split()))
arr2 = list(map(int,input().split()))

for i in arr1:
    llist1.append(i)

for i in arr2:
    llist2.append(i)

sol = ll.list_algorithms()

llist3 = ll.linkedlist()
llist3.head = sol.mergeTwoLists(llist1.head,llist2.head)
llist3.printLL()

Input:

  1 2 3
  2 3 4

Output:

  1 2 2 3 3 4

Communities/Hackathon/Conferences (In which the project was a part of)

FOSS Hack - 2020 (12th & 13th September 2020)	PyCon - 2020 Devsprint ( 04th & 05th October 2020)
Hacktoberfest 2020 (October 2020)	Winter of Code - DSC, NSEC

Latest Winter Update (Package Demo)

Tutorials

License

This package is under MIT License copyright @Abhijit Tripathy. The production code can be checked at the production branch of this repository.

Our sponsors

This project is supported by:

About The Creator

Abhijit Tripathy DSA Developer and Python Programmer

Our contributors

Made with contrib.rocks.

grokking-machine-learning's Issues

Cat vs Dog classification using CNN architecture

I would like to implement a Convolution Neural Network (CNN) architecture with ImageDataGenerator to classify whether an image contains either a dog or a cat.

@Abhijit2505 I'm participating in DWOC. It would be great if you assign this issue to me.
Thank you.

Integrate Welcome and Greeting Bot

Hi @Abhijit2505
I would like to contribute to this project by adding a welcome and greeting bot which will comment up when any user will open up with an issue or pull-request for the first time
Kindly do assign me this issue
( config file having a proper message)

For reference, kindly check out: https://github.com/apps/welcome

Decision Tree Classifier on Pima Indian Diabetes dataset

I would like to contribute this model

Predicting the stock prices using LSTM's and Tensorflow

I want to work on the predicting the stock price of a particular company using LSTM's . Can you please assign me this issue

ID3 Algorithm on Weather Dataset

@Abhijit2505 I would like to contribute this model to the repo.

UrbanSound8k

I would like to work on this dataset
https://zenodo.org/record/1203745

@Abhijit2505 Assign this to me as part of DWOC.
Assign this to me, and since the dataset is about 6GB. It will take me a while to complete it. About 2-3 days

Apple Stock price Prediction using Linear Regression

The model takes the input of the 'Apple' stock prices and outputs the prediction of the Closing price of the stock. It is implemented on Python using Linear Regression Models. Used the Quandl API to apply ML to the stock market.
Please label this issue as DWOC.
Also please add the level.

Wine Quality Classification

Need to classify wine quality dataset using sklearn or TensorFlow library

You can find the dataset at https://archive.ics.uci.edu/ml/datasets/wine+quality

Rain fall prediction in Australia

Dataset used: https://www.kaggle.com/jsphyg/weather-dataset-rattle-package
It contains about 10 years of daily weather observations from many locations across Australia.

Please label DWOC tag and the level.

Music Genre Classification with streamlit webapp

Music Genre classification using Convolutional Neural Networks. Implemented in Tensorflow 2.0 using the Keras API
Overview
tl;dr: Compare the classic approach of extract features and use a classifier (e.g SVM) against the Deep Learning approach of using CNNs on a representation of the audio (Melspectrogram) to extract features and classify. You can see both approaches on the nbs folder in the Jupyter notebooks.
and Streamlit web app is also built as interface to classify music genre along with visualisation

Multiple Linear Regression Model using Tensorflow

Add a Multiple linear regression model using Tensorflow framework.

Steps to follow

Comment about your interest in the issue and the dataset you want to work with
Tell us your approach in brief
Let the mentor respond to you and only after that get started with the issue.
Don't forget to check the already existing model in order to know the structure.

Join the discussion channel here - eduAlgo Community
Let's have a chat at the community tab before starting contributions.

Whatsapp Group Chat Analysis using NLP

Logically Weighted Regression for Non-linear Dataset

@Abhijit2505 i would like to work on this and contribute this model to the repo.

Logistic Regression using Tensorflow

Earthquake Prediction using XGBoost, CatBoost, and LGBM

@Abhijit2505 Kindly assign me this issue , i would like to use the following dataset to gather the data required to the train the model :
https://www.kaggle.com/c/LANL-Earthquake-Prediction

Twitter Sentiment Analysis using Natural Language Processing

Recreating MNIST handwritten digits using GAN, Tensorflow

I would like to apply Generative adversarial networks (GANs) to generate images from noise like in digits MNIST.
For the same, I will be using tf.keras.datasets module to load the MNIST dataset.

@Abhijit2505 I'm participating in DWOC. It would be great if you assign this issue to me.
Thank you.

Non-linear SVM using Tensorflow

Here we implement a multi-class classifier with SVM using non-linear kernels on the IRIS Dataset.

Simple Linear Regression Using Sci-kit learn

Add a simple linear regression model using sci-kit learn library.

Steps to follow

Comment about your interest in the issue and the dataset you want to work with
Tell us your approach in brief
Let the mentor respond to you and only after that get started with the issue.
Don't forget to check the already existing model in order to know the structure.

Join the discussion channel here - eduAlgo Community
Let's have a chat at the community tab before starting contributions.

Polynomial Regression model using Sci-kit Learn

Add a polynomial regression model using sci-kit learn library.

Steps to follow

• Comment about your interest in the issue and the dataset you want to work with
• Tell us your approach in brief
• Let the mentor respond to you and only after that get started with the issue.
• Don't forget to check the already existing model in order to know the structure.

Join the discussion channel here - eduAlgo Community
Let's have a chat at the community tab before starting contributions.

Hidden markov chains

i have build a model using hidden markov chains(rap generator). I am a DWOC participant

Implementing Evaluation metrics with python.

Will implement the following evaluation metrics with only python.

1. Classification Accuracy.
2. Confusion Matrix.
3. Mean Absolute Error.
4. Root Mean Squared Error.

A Study of the relations of the Brain to the Size of the Head using Machine learning algorithm.

A relation between head circumference and brain weight of humans is generally believed to exist.
I want to approach this problem and implement machine learning algorithm to establish a relationship between brain weight and head size.

@Abhijit2505 I'm participating in DWOC. It would be really nice if you assign this issue to me.
Thank you.

Simple Linear Regression with Tensorflow

Add a simple linear regression model using Tensorflow framework.

Steps to follow

• Comment about your interest in the issue and the dataset you want to work with
• Tell us your approach in brief
• Let the mentor respond to you and only after that get started with the issue.
• Don't forget to check the already existing model in order to know the structure.

Join the discussion channel here - eduAlgo Community
Let's have a chat at the community tab before starting contributions.

Better Readne.md

__A visually appealing Readme

Ridge Regression under Regularization

Ridge Regression under Regularization to handle underfitting or overfitting

KNN algorithm using scikit learn

GDP Growth of some common countries

What we can do is, we can use a dataset that will compute the GDP rates and then we can visualize it. Maybe we can use some predictive features for this program.

Multiple Linear Regression model using Sci-kit Learn

Add a multiple linear regression model using sci-kit learn library.

Steps to follow

• Comment about your interest in the issue and the dataset you want to work with
• Tell us your approach in brief
• Let the mentor respond to you and only after that get started with the issue.
• Don't forget to check the already existing model in order to know the structure.

Join the discussion channel here - eduAlgo Community
Let's have a chat at the community tab before starting contributions.

Titanic-Machine-Learning-from-Disaster

Using a Machine learning to create a model that predicts which passengers survived the Titanic shipwreck.
Here I will Use Titanic dataset from kaggle.

Naive Bayes Algorithm for Text Preprocessing

@Abhijit2505 I would like to contribute this model.

Fake News Detector using TfidfVectorizer

The fake news will be detected using TfidfVectorizer in python.
Please assign me this issue under DWOC and add labels.

Least Absolute Shrinkage and Selection Operator (LASSO)

Least Absolute Shrinkage and Selection Operator (LASSO) under Regularization

KNN using tensorflow

Add a KNN model using Tensorflow framework.

Steps to follow

Comment about your interest in the issue and the dataset you want to work with
Tell us your approach in brief
Let the mentor respond to you and only after that get started with the issue.
Don't forget to check the already existing model in order to know the structure.

Join the discussion channel here - eduAlgo Community
Let's have a chat at the community tab before starting contributions.

Implementation of KNN from Scratch without scikitlearn

Hii! Understanding ML algorithms from scratch is really significant while studying ML. I can add Implementation of KNN without using libraries, with proper comments for user to understand easily.

Kindly assign me this issue with label DWOC and Level- 4 or 5.

Handwritten Character Recognition with Neural Network

Classification of handwritten character recognition using Tensorflow

Dataset can be found at https://www.kaggle.com/sachinpatel21/az-handwritten-alphabets-in-csv-format

The Naive Bayes Classifier

The Naive Bayes Classifier model created using pandas python library and scikit-learn library.

CODE OF CONDUCT file

Hi,
I found that this project repository is not having a code of conduct file in this repository, kindly assign me this issue and I would like to contribute a well-formatted code of conduct file as you know code of conduct is a necessary file which the contributors need to follow so that everyone follows a decorum.

Predicting-Boston-House-Prices

Boston dataset is the one that a Machine learner should first do.
Here I will be predicting the prices.

Update Contributors Table in README.md File

Like this

Loan prediction problem

I would like to create a model to predict the eligibility for loan approval and deploy it with flask. Dataset is available on kaggle-https://www.kaggle.com/altruistdelhite04/loan-prediction-problem-dataset

Market Basket Analysis using Apriori Algorithm

Automating website

I would like to work on this issue.I will create a script that will enable opening website from CLI.
Please add DWOC label to it and assign me this issue.

Flight Price Prediction using ensemble algorithm

This project basically predicts the price of the flight by taking several parameters. This is a web application
Tech stack : Deeplearning,ML, flask
Dataset : from kaggle

Dimensionality Reduction Algorithms

Polynomial Regression

Polynomial Regression is a form of linear regression in which the relationship between the independent variable x and dependent variable y is modeled as an nth degree polynomial.
It is apparently the value between x and independent y

predicting whether a given tweet is about a real disaster or not?

Using NLP, we can analyze tweets. I would like to work on this. Dataset can be found on kaggle-https://www.kaggle.com/c/nlp-getting-started/overview

Traffic Signs Reognition Using CNN

I will train the dataset from Kaggle and make a CNN model for recognizing Traffic Signs. The accuracy of the model will be greater than 99%. @Abhijit2505 Kindly add the labels in this issue and assign it to me.

Implementing a Naive Bayes Classifier without any external libraries like scikit learn.

In this notebook/script I will be implementing Naive Bayes Classifier From Scratch in python will not be using any external library.
The implementation might be a bit lengthy but I could make it beginner friendly

Evaluation metrics for Regression and Classification

Most of the times many students don't know that on what metrics they should evaluate their model. I would like to work on this by taking one classification and one regression example.