sukanyabag/AUTOMATED-QUICK-EDA-WITH-SWEETVIZ-

Stars
3
Rank 3,963,521 (Top 79 %)
Language
HTML
Created over 4 years ago
Updated over 4 years ago

sukanyabag/AUTOMATED-QUICK-EDA-WITH-SWEETVIZ-

sukanyabag

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

INTRODUCTION TO PYTHON'S SWEETVIZ LIBRARY Sweetviz is an open source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with a single line of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Make sure you visit sweetviz.PyPI to explore more, and also consult and go through documentation of this library. DATASET USED FOR EDA : I have used train and test datasets from the "House Prices: Advanced Regression Techniques" competition hosted by KAGGLE, for performing the EDA. You can find the datasets at the following link redirected to KAGGLE : https://www.kaggle.com/c/house-prices-advanced-regression-techniques

DSA-and-ProblemSolving

Trying to cover the most asked coding questions at PBCs along with DSA implementations. (Striver + NeetCode SDE Sheet ONGOING)

Covid19-Detection-using-X-rays-Webapp

In this repo, you will see how to automatically detect COVID-19 in a hand-created X-ray image dataset using Keras, TensorFlow, and Deep Learning.

Jupyter Notebook

Detecting-Contradictions-and-Entailment-in-Multilingual-Text

A case study of NLI ( Natural Language Inferencing) with Transfer Learning. Kaggle Competition Rank - 18th (Global)

Jupyter Notebook

Text-Summarization-using-BERT-GPT2-XLNet

This notebook leverages Transfer Learning Algorithms and standard NLP procedures to summarize a given paragraph meaningfully.

Jupyter Notebook

Advance-REST-APIs-with-Flask

This repo is focused on developing RESTful APIs with Flask, SQLAlchemy, (de)/serializing with Marshmallow, advance email confirmations, image uploads, database migrations, third party login with OAuth, Incremental feature delivery and payments with Stripe. Read the API Documentation and play with the API in Postman here 👇

ML-DL-NLP-resource-notebooks

This repository contains all resources and notebook implementations of Machine Learning, Deep Learning and Natural Language Processing concepts.

Jupyter Notebook

DataCamp-Case-Studies

This repository contains the codes and datasets of various data science projects completed by me. These project tasks are a part of DataCamp's "Data Scientist with Python" career track.

Jupyter Notebook

Statistical-Analysis-of-My-Medium-Articles

This repository contains an exploratory data analysis of my writer data at Medium. I use it to carry out data analysis once in every 4 months to see audience and fan growth, and topics they love! You can check out the articles here👇

Jupyter Notebook

QnA-Langchain-VectorDB

An implementation of Retrieval Augmented Generation (RAG) to enhance Large Language Models for Document Q&A and Information Retrieval.

GCP-AI-Notebooks

This repository contains all practice notebooks with which I performed hands-on labs in Google Cloud Training Program's "Cloud ML-AI Track"

Jupyter Notebook

Transfer-Learning-Practice-Notebooks

In this repo I have demonstrated the implementations of various Transfer Learning pretrained model's architectures, that can be finetuned for one's specific usecase in Deep Learning/NLP.

Jupyter Notebook

Fake-News-Classifier--NLP

Jupyter Notebook

sukanyabag

Spam-Classifier-NLP-basic

Jupyter Notebook

Object-Oriented-Programming--Python

Contains implementations of all oop concepts in Python.

Stock-Market-Prediction-with-DeepL

Jupyter Notebook

Machine-Learning-Internship-Project---BG-Removal-WebApp

Contains the source code of developing a background removal app, with Google's TensorFlow.js BodyPix module. Implemented with JavaScript and Tensorflow framework (ML- internship Business Project)

Stock-Sentiment-Analysis---NLP

Jupyter Notebook

Notes-on-GPT-2-and-BERT-models

Jupyter Notebook

Microsoft-Malware-Detection

Advanced ML Case Study where we use ML algorithms to detect malware from a given piece of software.

Jupyter Notebook

Data-Analysis-Internship

Jupyter Notebook

Movie-Recommendation-System

A data driven AI movie recommendation system application that leverages Machine Learning to recommend movies to users, based on their likes.

Jupyter Notebook

COVID19-EDA-INDIA

COVID-19 is an infectious disease caused by the Corona Virus, biologically known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was first identified in Wuhan, the capital of China's Hubei province in December 2019 and has spread all over the world since then. As of writing this, on 26th April 2020, 21:57 IST, there are 2.92 million confirmed cases throughout the world and has resulted in 204,000 deaths according to Google. In this notebook, I will take a look at the current situation in India. We will take a look at the regions which are most hampered by the outbreak and how numbers have steadily climbed in the country. PROGRAMMING LANGUAGE AND MODULES INCLUDED IN THIS PROJECT : PROGRAMMING LANGUAGE - Python 3x(3.7.8) PYTHON LIBRARIES - Numpy, Pandas, Matplotlib, Seaborn Author - Sukanya Bag Project done during - 1st July 2020 to 5th July 2020

Jupyter Notebook

Quora-Question-Pair-Similarity-CaseStudy

Identify which questions asked on Quora are duplicates of questions that have already been asked. We are tasked with predicting whether a pair of questions are duplicates or not. We are talking about the semantic similarity of the questions.

Jupyter Notebook

Alexa-Reviews-Sentiment-Analysis

This repository's notebook provides the insight of customer reviews on Amazon's kid Alexa, by data visualization, sentiment analysis and classification using NLP techniques.

Jupyter Notebook

CREDIT-CARD-ANOMALY-DETECTION

Machine Learning - Credit Card Fraud Detection Introduction The objective in this project is to build machine learning models to classify or identify fraudulent card transactions from a given card transactions data. Data Description The dataset contains two-days credit card transactions made in September 2013 by European cardholders. The dataset is highly unbalanced with a low percentage of fraudulent transactions within several records of normal transactions. The positive class (frauds) account for 0.172% (492 frauds out of 284,807 transactions) of all transactions. Features V1, V2, ... V28 are the principal components obtained with PCA, the only features which have not been transformed with PCA are 'Time' and 'Amount'. Feature 'Time' contains the seconds elapsed between each transaction and the first transaction in the dataset. Feature 'Class' is the target variable with value 1 in case of fraud and 0 otherwise. Dataset source - Kaggle Author - Sukanya Bag , Date - 1st July, 2020

Jupyter Notebook

Dart-Programming-Samples

Repo contains Dart code samples useful for learning Dart.

Java-OOP-Lab-Programs

This repo contains some boring java programs. Never mind 😑

Pose-Estimator-AI-App

This AI driven flutter application detects pose in real-time environment. It leverages Google's PoseNet Model which comes with TensorFlow.js.