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Andrea Manero-Bastin's Blog – November 2019 Archive (5)

Deep Learning from first principles in Python, R and Octave – Part 1

This article was written by Tinniam V Ganesh.

 

This is the first in the series of posts, I intend to write on Deep Learning. This post is inspired by the Deep Learning Specialization by Prof Andrew Ng on Coursera and Neural Networks for Machine Learning by Prof Geoffrey Hinton also on Coursera.…

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Added by Andrea Manero-Bastin on November 30, 2019 at 9:00am — No Comments

How to build a deep learning model in 15 minutes

This article was written by Montana Low. 

 

An open source framework for configuring, building, deploying and maintaining deep learning models in Python.

As Instacart has grown, we’ve learned a few things the hard way. We’re open sourcing Lore, a framework to make machine learning approachable for Engineers and maintainable for Machine Learning Researchers.…

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Added by Andrea Manero-Bastin on November 30, 2019 at 9:00am — No Comments

Beginners Guide To Statistical Cluster Analysis

This article was written by Mohammad Sajid.

 

Statistical cluster analysis is an Exploratory Data Analysis Technique which groups heterogeneous objects(M.D.) into homogeneous groups. We will learn the basics of cluster analysis with mathematical way.

Cluster Analysis can be done by two…

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Added by Andrea Manero-Bastin on November 30, 2019 at 8:30am — No Comments

Introduction to Markov Chains

This article was written by Devin Soni.  

 

Markov chains are a fairly common, and relatively simple, way to statistically model random processes. They have been used in many different domains, ranging from text generation to financial modeling. A popular example is r/SubredditSimulator, which uses Markov chains to automate the creation of content for an entire subreddit. Overall, Markov Chains are conceptually quite intuitive,…

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Added by Andrea Manero-Bastin on November 18, 2019 at 5:00am — 1 Comment

New Theory Cracks Open the Black Box of Deep Learning

This article was written by Natalie Wolchover.

 Even as machines known as “deep neural networks” have learned to converse, drive cars, beat video games and Go champions, dream, paint pictures and help make scientific discoveries, they have also confounded their human creators, who never expected so-called “deep-learning”…

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Added by Andrea Manero-Bastin on November 1, 2019 at 5:30am — No Comments

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