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Analytics Vidhya for iOS

Analytics Vidhya is India's largest and the world's 2nd largest data science community.

We aim to help you learn concepts of data science, machine learning, deep learning, big data & artificial intelligence (AI) in the most interactive manner from the basics right up to very advanced levels.

Analytics Vidhya app provides high quality learning resources for data science professionals, data engineers and students who want to study data science and machine learning algorithms, along with codes.

Some of the popular posts on the app

A Comprehensive Learning Path for Deep Learning in 2019

The Ultimate Learning Path to Become a Data Scientist and Master Machine Learning in 2019

A Complete Tutorial to Learn Data Science with Python from Scratch

Essentials of Machine Learning Algorithms (with Python and R Codes)

An Introduction to Implementing Neural Networks using TensorFlow

A Complete Guide on Getting Started with Deep Learning in Python

Tips and Tricks to Ace Data Science Interviews

7 Types of Regression Techniques you should know!

A Complete Tutorial on Ridge and Lasso Regression in Python

Deep Learning Tutorial to Calculate the Screen Time of Actors in any Video (with Python codes)

Comprehensive Introduction to Apache Spark, RDDs & Dataframes (using PySpark)

A Simple Introduction to Facial Recognition (with Python codes)

30 Questions to test your understanding of Logistic Regression

A Complete Tutorial on Tree Based Modeling from Scratch in R & Python

The most comprehensive Data Science learning plan

6 Easy Steps to Learn Naive Bayes Algorithm (with codes in Python and R)

Top 28 Cheat Sheets for Machine Learning, Data Science, Probability, SQL & Big Data

Solving Multi-Label Classification problems (Case studies included)

Understanding Support Vector Machine algorithm from examples (along with code)

Architecture of Convolutional Neural Networks (CNNs) demystified

Complete Guide to Parameter Tuning in XGBoost (with codes in Python)

Practicing Machine Learning Techniques in R with MLR Package

Heroes of Deep Learning: Top Takeaways for Aspiring Data Scientists from Andrew Ngs Interview Series

Machine Learning and Deep Learning Algorithms:

Linear and Logistic Regressions

NaiveBayes

Neural Networks

Decision Trees

Convolutional Neural Networks

Long Short Term Memory Recurrent Neural Networks

SVM (Support Vector Machines)

Restricted Boltzmann Machines

Restricted Boltzmann Machines

Learn libraries and tools:

Pandas

Matplotlib

Scikit-learn

TensorFlow

Caffe

PyTorch

XGBoost

eras

PySpark

Top categories & topics

Data Science

Big data

Business analytics

Deep learning

Machine learning

NLP (Natural Language Processing)

Reinforcement Learning

Neural Network (Traditional and Convolutional)

Supervised Learning

Unsupervised Learning

Modeling in Python and R

Time Series Analysis

Data Engineering

We have more than 200,000 registered users to our blog and newsletter and more than 2.4 million monthly visits on our portal. People engage on Analytics Vidhya to learn from thought leaders and industry experts, participate in hiring, branding & problem solving/crowd sourcing hackathons on our Global DataHack Platform ( https://datahack.analyticsvidhya.com/contest/all/) in areas such as Artificial Intelligence, Machine Learning , Data Engineering, Data Mining and Advanced Analytics, and also engage in discussions to share ideas and solve data related business problems for organisations. Over the past 2 years we have engaged in more than 60 hackathons with some of the leading global companies in the world & in India. We also have a dedicated platform for courses (https://trainings.analyticsvidhya.com/) created by the best in data science where you can enroll in courses and sharpen your skillset.

Privacy: https://www.analyticsvidhya.com/privacy-policy/

Terms: https://www.analyticsvidhya.com/terms/

Full Specifications

What's new in version

General

Release January 17, 2020
Date Added January 17, 2020

Operating Systems

Operating Systems iOS
Additional Requirements Requires iOS 9.0 or later. Compatible with iPhone, iPad, and iPod touch.

Popularity

Total Downloads 0
Downloads Last Week 0
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