Tag: neural networks

The Open Source Data Science Masters

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“The open-source curriculum for learning Data Science. Foundational in both theory and technologies, the OSDSM breaks down the core competencies necessary for making use of data. The Internet is Your Oyster. With Coursera, ebooks, Stack Overflow, and GitHub — all free and open — how can you afford not to take advantage of an open source education?” This program consists of a list of courses and resources. The curriculum covers: … Continue Reading

Data Science from Scratch: First Principles with Python

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From Amazon: “Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get … Continue Reading

JuliaCon


2017 Event:  June 20th-24th – Berkeley, CA Accepted Talks and Workshops for 2017 Videos from JuliaCon 2016  

DataCamp – Deep Learning in Python

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From DataCamp: “Artificial neural networks (ANN) are a biologically-inspired set of models that facilitate computers learning from observed data. Deep learning is a set of algorithms that use especially powerful neural networks. It is one of the hottest fields in data science, and most state-of-the-art results in robotics, image recognition and artificial intelligence (including the famous AlphaGo) use deep learning. In this course, you’ll gain hands-on, practical knowledge of how to … Continue Reading

NIPS (Neural Information Processing Systems) Conference

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From NIPS Conference site: “The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS) is a multi-track machine learning and computational neuroscience conference that includes invited talks, demonstrations, symposia and oral and poster presentations of refereed papers. Following the conference, there are workshops which provide a less formal setting” Next event:  December 4 – 9, 2017 – Long Beach, CA Registration begins September 1, 2017 Videos from NIPS Conference 2016: NIPS … Continue Reading

The Elements of Statistical Learning

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This book describes the important ideas in statistics, data mining, machine learning, and bioinformatics in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics.

Pattern Recognition and Machine Learning

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This textbook is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics, and is aimed at advanced undergraduates or 1st-year PhD students, as well as practitioners.

Data Science from Scratch: First Principles with Python

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In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

Linear Digressions

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We’re producing this podcast because machine learning is exciting!

Predictive Analytics 2 – Neural Nets and Regression

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In this online course, you will continue work from Predictive Analytics 1, and be introduced to additional techniques in predictive analytics, also called predictive modeling, the most prevalent form of data mining.