New Machine Learning Cheat Sheet by Emily Barry

#MachineLearning Cheat Sheet, the #emoji edition:  #abdsc #BigData #DataScience #AI

  • This blog about machine learning was written by Emily Barry.
  • Emily is a Data Scientist in San Francisco, California.
  • The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time.
  • This is by no means a comprehensive guide to machine learning, but rather a study in the basics for herself and the likely small overlap of people who like machine learning and love emoji as much as she do.
  • For more articles about machine learning, click here.

This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
Continue reading “New Machine Learning Cheat Sheet by Emily Barry”

Book: Data Science for the Layman: No Math Added

#DataScience Book for the Layperson:  #abdsc #BigData #DataAnalytics #MachineLearning #AI

  • Want to get started on data science?
  • This book has been written in layman’s terms as a gentle introduction to data science and its algorithms.
  • Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application.
  • With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

Want to get started on data science? Our promise: no math added.
This book has been written in layman’s terms as a gentle introduction to data science and its…
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A Designer’s Guide To The $15 Billion Artificial Intelligence Industry

A designer's guide to the $15 billion artificial intelligence industry  (from 2016)

  • The best designers know that they need to study human behavior if they want to make the right choices for their users.
  • It allows designers to cater to, and anticipate, individual users’ needs.
  • With AI, products and services aren’t just performing basic functions; they’re emotionally aware, letting designers create the best experience for each user.
  • Psychology: The way an AI system communicates with users at 2 p.m. should be different from the way it talks to them at 2 a.m., taking into account the unusually late time and understanding that the users are likely frustrated because they can’t sleep, playful because they’ve been drinking, or panicked because there’s been an emergency.
  • Designers have to understand the many ways users might react in different scenarios and how they will express their intention depending on factors like their mood, location, and what they ate that day.

As artificial intelligence gains ground, designers will need to adapt. Here’s how to get started.

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New Machine Learning Cheat Sheet by Emily Barry

New #MachineLearning Cheat Sheet by Emily Barry #abdsc

  • This blog about machine learning was written by Emily Barry.
  • Emily is a Data Scientist in San Francisco, California.
  • The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time.
  • This is by no means a comprehensive guide to machine learning, but rather a study in the basics for herself and the likely small overlap of people who like machine learning and love emoji as much as she do.
  • For more articles about machine learning, click here.

This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
Continue reading “New Machine Learning Cheat Sheet by Emily Barry”

Rise Up and Meet the Data Science Competition

Rise Up and Meet the #DataScience Competition - 
#analytics #ai #bigdata

via @MktgSciences

  • So when a group of data scientists get together, it’s natural that a little good-natured competition breaks out, to see who can best solve a particular challenge, for both ever-lasing glory and cash prizes.
  • Here are nine on-going data science competitions that might interest data scientists:

    Impetus Technologies is giving away $20,000 in prize money to data science teams that can best utilize Spark Streaming within the construct of its StreamAnalytix product to build real-time streaming applications.

  • MZ is putting up $1 million in prize money for its Satori Challenge, which pits developers against one another in a competition to build the most impactful live data channel on Sartori, the name of MZ’s new open data platform.
  • CrowdAnalytix is putting up $4,500 in prize money this competition, which pits data scientists against each other to find out who can more accurately identify a theme from a group of images.
  • There’s no prize money in this DrivenData competition, just ever-lasting glory for those keen data types who can figure out how to identify which Tanzanian water pumps are working and which aren’t from telemetry data consisting of about 40 distinct variables.

Data scientists love challenges. So when a group of data scientists get together, it’s natural that a little good-natured competition breaks out, to see wh
Continue reading “Rise Up and Meet the Data Science Competition”

New Machine Learning Cheat Sheet by Emily Barry

Machine Learning Cheat Sheet

  • This blog about machine learning was written by Emily Barry.
  • Emily is a Data Scientist in San Francisco, California.
  • The more she learns about machine learning algorithms, the more challenging it is to keep these subjects organized in her brain to recall at a later time.
  • This is by no means a comprehensive guide to machine learning, but rather a study in the basics for herself and the likely small overlap of people who like machine learning and love emoji as much as she do.
  • For more articles about machine learning, click here.

This blog about machine learning was written by Emily Barry. Emily is a Data Scientist in San Francisco, California. She really loves emoji. Another thing she…
Continue reading “New Machine Learning Cheat Sheet by Emily Barry”

OracleVoice: Machine Learning Stands To Transform The Way We Communicate

OracleVoice: Machine learning stands to transform the way we communicate

  • With adaptive intelligent applications, organizations can also begin to offer personalized recommendations to customers by getting to the heart of their individual business needs, purchasing decisions, interests, and patterns.
  • New Oracle Cloud services can provide employees with a knowledge base that provides the insights they need to improve business results through a heightened understanding of the way their customers operate.
  • These adaptive intelligent applications can provide organizations—from finance professionals and HR recruiters to marketing and supply chain managers—with actionable business and customer insights to make more informed decisions, leading to more success for their customers.
  • While customer success has long been a central component in the DNA of many organizations, adaptive intelligent applications are helping business integrate customer success further into the DNA of the devices their clients and employees rely on daily.
  • Then, businesses can truly begin to transform the way they anticipate customers’ needs and provide unrivaled experiences and unmatched success.

With adaptive intelligent applications, organizations can offer personalized recommendations to customers by getting to the heart of their individual business needs, purchasing decisions, interests, and patterns.
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