Rajendra

I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...

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I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing

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12 Useful Data Science Walkthroughs

By Rajendra |Email | Jul 26, 2017 | 6729 Views

So you have developed some base skills in programming, data visualization, data manipulation etc... And are looking for ways to apply those skills and build a data science portfolio?

We are here to help.
Practicing your skills with concrete examples will boost your data science confidence and will help you identify and solve problems in the real world. For this reason, we have made a collection of high-quality walkthroughs ranging from Text Mining, ML, Deep Learning, Finance and more.

Check it out and let us know your favorite!

Text Mining in R
  • In this 3-part tutorial, you will learn how to scrape H-1B visa data with R. DataCamp instructor Ted Kwartler walks you through how to parse and store the JSON data, perform Exploratory Data Analysis, adding visuals, and finally create a map of the data thanks to a geocoding API. This walkthrough is valuable as it shows all the steps a data scientist would take to answer a question: Can Data Help Your H-1B Visa Application?
  1. Part 1: Web Scraping and Parsing Data
  2. Part 2: Adding visuals to your EDA
  3. Part 3: Geocode Location & Create a Map of the Data                                                                                      

Data Mining (Python)
Introduction to Market Basket Analysis in Python - learn how to use market basket analysis to find common patterns of items in large datasets. This walkthrough showcases this technique on a large online retail data set to try to find interesting purchase combinations.



Machine Learning
Machine Learning (ML) is increasingly becoming essential in a data scientist toolbox for both R and Python. Advances in ML are a big reason why data science has become such an in-demand skill. These 3 walkthroughs below show you how to use scikit-learn (Python) and Caret (R) along with a series of Machine Learning techniques.

Scikit-Learn (Python)

  • Python Machine Learning: Scikit-Learn Tutorial - This introductory post covers the basics of scikit-learn using digits data. The techniques covered here are Principal Component Analysis (PCA), Support Vector Machines (SVM), and K-Means algorithms.

  • Scikit-Learn Tutorial: Baseball Analytics - This 2-part walkthrough uses baseball datasets to determine Major League Baseball (MLB) Teams wins per season based on team statistics, and which player will be voted into the Hall of Fame based on career statistics and awards. The techniques covered here are Linear Regression, K-Means, Logistic Regression, and Random Forest.

  1. Part 1: Predicting MLB Teams Wins per Season
  2. Part 2: Which Player will be Voted into the Hall of Fame

Caret (R)
  • Machine Learning in R For Beginners - This includes a walkthrough on multi-class classification with the well-known k-nearest neighbor algorithm with the help of the caret library. This short introduction to ML in R is a must for R learners and the data used here is the famous iris dataset.

Building a Classifier

Forecasting (Python)



Deep Learning
Even more so than Machine Learning, Deep Learning gets all the attention in the data science world. Companies are investing in infrastructure and talent to take advantage of this new field. To become an elite data scientist, Deep Learning is a must.

Keras (R + Python)


  • keras: Deep Learning in R - The Keras package was recently launched in R, be an early adopter! Here you will build a MLP for multi-class classification again using the iris dataset.

TensorFlow



Finance (Python)
Python For Finance: Algorithmic Trading - Perform financial analysis, develop a trading strategy, and backtest it using Quantopian in this popular walkthrough.




Source: Datacamp