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All Blog Posts Tagged 'dsc_resource' (29)

KDNuggets.com Launches Free Outlier Analysis Boxplot Template

Visit the KDNuggets.com Statistics page and download a free outlier analysis boxplot template from the Topics section. Boxplot analysis can solve business analysis problems. This free…

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Added by Tom Wolfer on July 28, 2021 at 3:30am — 5 Comments

A must have tool to analyse latest AI research papers fast

Here is a great too for your AI research

I feel like a kid in a candy shop! 

If you are like me, and want to stay on top of AI, you spend a lot of time working through research papers

However, there is no tool which can show you great new research in AI in near real time

So, it was great to find this free and open source…

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Added by ajit jaokar on July 4, 2021 at 3:00am — 2 Comments

Applications of Deep Neural Networks 575 page free book by Jeff Heaton

If you want some holiday reading, here is something for you 

I think  this is extraordinarily generous 

Applications of Deep Neural Networks 575 page free book by Jeff Heaton 

TOC below download links at the end of the post

Happy holidays :)  

0.1 Introduction . . . .…

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Added by ajit jaokar on December 24, 2020 at 1:31pm — No Comments

Free 500 page + book on Applications of Deep Neural Networks

Applications of Deep Neural Networks is a free 500 + page book by Jeff Heaton

The contents are as below

The download link is at the bottom of the page

Introduction                                               

 Python Preliminaries

  • Assignments…
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Added by ajit jaokar on December 7, 2020 at 5:42am — No Comments

A taxonomy of explainable (XAI) AI models

I am reading a very interesting paper called Principles and Practice of Explainable Machine Learning by

Vaishak Belle (University of Edinburgh & Alan Turing Institute) and Ioannis Papantonis (University of Edinburgh) which presents a taxonomy of explainable AI (XAI).

 

XAI is a complex subject…

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Added by ajit jaokar on November 6, 2020 at 2:00pm — No Comments

Free book - Cloud Native, Containers and Next-Gen Apps

 

I always seek good resources for my teaching at #universityofoxford and this is a great free book on Cloud native – a topic that is very much in the focus

 

The book needs a free registration and is provided as a full ebook by d2iq.

 

D2iq was formerly mesosphere – the commercial arm of mesos – but…

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Added by ajit jaokar on October 19, 2020 at 1:32pm — No Comments

Free book - Artificial Intelligence: Foundations of Computational Agents

Free book - Artificial Intelligence: Foundations of Computational Agents

There are many excellent free books on Python – but Artificial Intelligence: Foundations of Computational Agents is about  a subject not commonly covered

I found the book useful as a introduction to Reinforcement Learning

As the title…

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Added by ajit jaokar on October 1, 2020 at 2:00pm — No Comments

Free online book - Machine Learning from Scratch

Hi all,

I'm writing to share a book I just published that I think many of you might find interesting or useful. 

The book is called "Machine Learning from Scratch." It provides complete derivations of the most common algorithms in ML (OLS, logistic regression, naive Bayes, trees, boosting, neural nets, etc.) both in theory and math. It also demonstrates constructions of each of these methods from scratch in Python using only numpy.



My aim with the…

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Added by Daniel Friedman on September 3, 2020 at 1:00pm — No Comments

A Programming Guide with Probability and Statistics

Probability and Statistics- the terms which resonate together to create the vast applications of the fields of Data Science and Machine Learning, have immensely grown a huge followers’ base in this era. But programming the concept sometimes gets tricky and requires a lot of contemplation on the code. Allen B. Downey, in his ‘Think’ series has written a book to solve just the problem for everyone.…

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Added by Andrea Manero-Bastin on August 25, 2020 at 5:30am — No Comments

Probability: Syllabus, Cambridge University

Course material for Richard Weber's course on Probability for first year mathematicians at Cambridge. You can also check Richard's blog (a former colleague of my dad) here. It also includes exams question. This is the base material that needs to be mastered before being accepted in the prestigious Tripo III curriculum at Cambridge. The book (PDF) can be downloaded…

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Added by Capri Granville on August 23, 2020 at 1:30pm — No Comments

Machine Learning vs. Statistics

Originally posted here.

Added by Vincent Granville on August 20, 2020 at 1:09pm — No Comments

Machine Learning vs. Statistics

This article was written by Tom Fawcett and Drew Hardin.

Throughout its history, Machine Learning (ML) has coexisted with Statistics uneasily, like an ex-boyfriend accidentally seated with the groom’s family at a wedding reception: both uncertain where to lead the conversation,…

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Added by Andrea Manero-Bastin on August 18, 2020 at 11:00am — No Comments

How to approach the study of algorithms?

 

I have been reading a book recently about algorithms in the wider sense

(40 algorithms every programmer should know -book and github link below)

 

I spend a lot of time with algorithms considering my teaching (AI at University of Oxford).

For Machine Learning and Deep Learning, we need to study a…

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Added by ajit jaokar on July 16, 2020 at 3:30am — No Comments

Free book – for #datascience interviews - Guide to competitive programming

Recently Springer made some good books on maths free to download.

Competitive programming strategies are useful for many data science interviews and they help to improve your maths foundations.  There are not many books on this subject (although there are many good websites and YouTube resources).

So, I hope you find this book…

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Added by ajit jaokar on June 23, 2020 at 12:00pm — 5 Comments

A free self-paced learning path for #machinelearning and #deeplearning

In various formats, one of the most frequent questions I am asked is the equivalent of:

“Can you recommend a free self-paced learning path for #machinelearning and #deeplearning?”

In this post, I attempt an answer

This is based on my work / teaching students primarily at Oxford University, but I…

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Added by ajit jaokar on May 26, 2020 at 1:59pm — No Comments

Free book on Statistics: Larry Wasserman’s All of Statistics

One of the best-known books on statistics is now free

Larry Wasserman’s All of Statistics is free to download from Springer

I like this book because – unlike most books on statistics - it takes a modern approach to statistics and covers…

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Added by ajit jaokar on April 27, 2020 at 3:17pm — No Comments

Book: [email protected] - The greatest data stories ever told!

My new ebook about Agile, AI, data, deep learning, IT and much more.

Highly polemic, contrarian and insightful. It informs, educates and entertains. It incites thought, reflection and reassessment. It’s delightfully seductive, easy to read and hard to put down. And there’s a lot of it. So, you won’t be left…

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Added by Martyn Jones on April 23, 2020 at 9:30pm — 3 Comments

50 Must-Read Free Books For Every Data Scientist in 2020

50 Must-Read Free Books For Every Data Scientist in 2020

Data science is an inter-disciplinary field which contains methods and techniques from fields like statistics, machine learning, Bayesian etc. They all aim to generate specific insights from the…

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Added by Ayush Srivastava on April 6, 2020 at 3:00am — No Comments

The difference between Statistics and Data Science: Big Data and Inferential Statistics

This post is based on two insightful threads I read online (References below)

Based on these, I address the question of ‘The difference between Statistics and Data Science’. Traditionally, most people, including me, would say that ‘statistics came first and Data Science builds upon statistics’. This chain of thought is valid but as you see…

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Added by ajit jaokar on February 23, 2020 at 11:49am — No Comments

25 Great Articles and Tutorials on Classification Methods

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

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Added by Vincent Granville on February 10, 2020 at 8:30am — No Comments

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