10 Algorithms Every Programmer Should Know – and When to Use Them

@tachyeonz : Programmers love algorithms. What’s an algorithm? Good question! In my academic days, we would have said, “An algorithm is a well-defined, self-contained process or set of rules to be followed in a data processing system.”

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Machine Learning Explained: Algorithms Are Your Friend

@tachyeonz : We hear the term “machine learning” a lot these days, usually in the context of predictive analysis and artificial intelligence. Machine learning is, more or less, a way for computers to learn things without being specifically programmed. But how does that actually happen?

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An overview of gradient descent optimization algorithms

@tachyeonz : Gradient descent is one of the most popular algorithms to perform optimization and by far the most common way to optimize neural networks. At the same time, every state-of-the-art Deep Learning library contains implementations of various algorithms to optimize gradient descent (e.g.

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The Contextual Bandits Problem: A New, Fast, and Simple Algorithm

@tachyeonz : We study the general problem of how to learn through experience to make intelligent decisions. In this setting, called the contextual bandits problem, the learner must repeatedly decide which action to take in response to an observed context, and is then permitted to observe the received reward, but

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The Algorithms Behind Probabilistic Programming

@tachyeonz : We recently introduced our report on probabilistic programming. The accompanying prototype allows you to explore the past and future of the New York residential real estate market.

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41 Essential Machine Learning Interview Questions (with answers)

@tachyeonz : Machine learning interview questions are an integral part of the data science interview and the path to becoming a data scientist, machine learning engineer or data engineer.

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140 Machine Learning Formulas

@tachyeonz : By Rubens Zimbres. Rubens is a Data Scientist, PhD in Business Administration, developing Machine Learning, Deep Learning, NLP and AI models using R, Python and Wolfram Mathematica. Click here to check his Github page.

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Becoming a Data Scientist

@tachyeonz : This blogpost is an excerpt of Springboard’s free guide to data science jobs and originally appeared on the Springboard blog. Most data scientists use a combination of skills every day, some of which they have taught themselves on the job or otherwise. They also come from various backgrounds.

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What I Learned Implementing a Classifier from Scratch in Python

@tachyeonz : This post is part of the Learning Machine Learning series. It’s based on Chapter 1 and 2 of Python Machine Learning. Machine learning can be intimidating for a newcomer. The concept of a machine learning things alone is quite abstract. How does that work in practice?

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Notes and terminology definitions for the machine learning algorithm cheat sheet

@tachyeonz : The suggestions offered in this algorithm cheat sheet are approximate rules-of-thumb. Some can be bent, and some can be flagrantly violated. This is intended to suggest a starting point. Don’t be afraid run a head-to-head competition between several algorithms on your data.

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Why big data and algorithms won’t improve business strategy

@tachyeonz : Each player takes it in turn to press a piece. Each player is aware of what piece the other player pressed. White starts first. Then Black counters, then White, then Black and so the game continues building up the sequence of presses.

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Stanford Lecture: Don Knuth’s Christmas Tree Lecture 2016

@tachyeonz : Computer Musings 2016Donald Knuth’s Christmas Tree LectureSpeaker: Donald KnuthAbout 1850, William Rowan Hamilton invented the Icosian Game, which involved finding a path that encounters all points of a network without retracing its steps. Variants of his game have turned out to be important in man

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