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기술
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 Ng’s 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/
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