Emmanuelle Rieuf's Blog – August 2016 Archive (15)

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

This article on Machine Learning Algorithms was posted by Sunil Ray from Analytics Vidhya. Sunil is a Business Analytics and Intelligence professional with deep experience in the Indian Insurance industry.

Sunil has created this guide to simplify the journey of aspiring data scientists and machine learning enthusiasts across the world. Through this guide, he will enable you to…


Added by Emmanuelle Rieuf on August 30, 2016 at 9:30am — No Comments

25 Java Machine Learning Tools & Libraries

This article about java machine learning tools & libraries comes from BDAN Big Data Analytics News. BDAN's site consists information on business trends, big data use cases, big data news to help you learn what Big Data is and how it can benefit organizations of all sizes.

Here is a list of 10 Java Machine learning tools & libraries:…


Added by Emmanuelle Rieuf on August 30, 2016 at 9:30am — No Comments

Book: Python Machine Learning Blueprints

Key Features

  • Put machine learning principles into practice to solve real-world problems
  • Get to grips with Python's impressive range of Machine Learning libraries and frameworks
  • From retrieving data from APIs to cleaning and visualization, become more confident at tackling every stage of the data pipeline



Added by Emmanuelle Rieuf on August 24, 2016 at 11:00am — No Comments

Statistical analysis in Google Sheets

This article was originally posted here. It was written by Steven Scott, a Bayesian statistician interested in data augmentation methods and Markov chain Monte Carlo. Steven has applied these methods to problems in educational testing, network security, biometrics, web browsing, e-commerce, and medical applications.…


Added by Emmanuelle Rieuf on August 24, 2016 at 10:30am — No Comments

Book: Data Science Essentials in Python

Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learning, and network analysis; process numeric data with the NumPy and Pandas modules; describe and analyze data using statistical and…


Added by Emmanuelle Rieuf on August 23, 2016 at 9:00am — No Comments

Top 10: Data Science and Machine Learning Articles in July

This article was originally posted here by Mike Tamir. Mike is a seasoned data science leader, who builded data science teams specializing in machine learning, data architecture, and predictive analytics solutions.

Top 10 most popular posts in…


Added by Emmanuelle Rieuf on August 23, 2016 at 8:30am — No Comments

Book: Statistics for Non-Statisticians

  • Aimed at practitioners
  • The presentation is as non-mathematical as possible
  • Includes many examples of the use of statistical functions in spreadsheets
  • Employs a realistic sample survey as an exemplar throughout the book
  • Fills a gap in the existing literature on…

Added by Emmanuelle Rieuf on August 22, 2016 at 4:00pm — No Comments

An absolute beginner’s guide to machine learning, deep learning, and AI

This article was posted by SmileJet on Dev Battles.

Meet Samantha. She’s your friendly assistant from 2025. She sorts your mail, sets up your meetings, and orders groceries. She paints and writes poetry. She’s your best friend. She’s also an artificial intelligence from the movie Her, which imagines how a juiced-up Siri will change our lives.

Now, tech companies large and small are racing to make this a reality. You’ve read the news. You’ve heard the jargon: AI,…


Added by Emmanuelle Rieuf on August 20, 2016 at 5:30pm — No Comments

Coding Explained in 25 Profound Comics

This article was published on Free Code Camp. Free Code Camp publish stories about development, design, data science, and open source. They asked their open source community to share the comics they found most profoundly described coding, via their news site (on Reddit.)

Here are their 25 most upvoted comics:



Added by Emmanuelle Rieuf on August 20, 2016 at 4:30pm — No Comments

Python: Getting Started with Data Science

This post was written by Dallin Akagi and Mark Steadman.

This short tutorial will not only guide you through some basic data analysis methods but it will also show you how to implement some of the more sophisticated techniques available today. We will look into traffic accident data from the National Highway Traffic Safety Administration and try to predict fatal accidents using state-of-the-art statistical learning techniques.  If you are…


Added by Emmanuelle Rieuf on August 20, 2016 at 4:30pm — No Comments

Book: Systems Analytics: Adaptive Machine Learning workbook

SYSTEMS Analytics title refers to a new development effort in the field of Machine Learning grounded firmly in Systems Theory; the subtitle, “ADAPTIVE Machine Learning”, captures the link to the current state of the art. My intention in writing this book is to bring mathematically trained graduates in engineering, physics, mathematics and…


Added by Emmanuelle Rieuf on August 10, 2016 at 8:30am — No Comments

Supervised Learning - Comprehensive Tutorial (Python-based)

This article is from Scikits learn. Scikit-learn Machine Learning in Python is simple and efficient tools for data mining and data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable - BSD license. …


Added by Emmanuelle Rieuf on August 8, 2016 at 2:30pm — No Comments

Book: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (MIT Press)

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important…


Added by Emmanuelle Rieuf on August 5, 2016 at 11:00am — No Comments

10 Algorithm Categories for A.I., Big Data, and Data Science

This article was written by a Data-centric Executive Management, Chris Pehura. Chris is a management consultant with a data emphasis helping Fortune 100/1000 companies strategically evolve and reinvent their businesses to maximize their revenue growth.

Are algorithms taking over our jobs? Yes, yes they are… and that a good thing.

An algorithm is a series of steps with rules that help us solve problems and accomplish goals. And when we structure…


Added by Emmanuelle Rieuf on August 4, 2016 at 10:00am — No Comments

My Top 9 Favorite Python Deep Learning Libraries

This article was posted by Adrian Rosebrock on Pyimagesearch. Adrian is an entrepreneur and Ph.D who has launched two successful image search engines, ID My Pill and Chic Engine.

Inside this blog post, he details 9 of his favorite Python deep learning libraries. This list is by no means exhaustive, it’s simply a…


Added by Emmanuelle Rieuf on August 3, 2016 at 2:30pm — No Comments

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