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Machine Learning Using R

Machine Learning Using R

Machine Learning Using R by Karthik Ramasubramanian
English | 12 Jan. 2017 | ISBN: 1484223330 | 568 Pages | PDF | 11.47 MB

This book is inspired by the Machine Learning Model Building Process Flow, which provides the reader the ability to understand a ML algorithm and apply the entire process of building a ML model from the raw data.

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Machine Learning Using R by Karthik Ramasubramanian

Machine Learning Using R by Karthik Ramasubramanian

Machine Learning Using R by Karthik Ramasubramanian
English | 10 Jan. 2017 | ISBN: 1484223330 | 592 Pages | EPUB | 8 MB


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Jose Unpingco - Python for Probability, Statistics, and Machine Learning (EPUB)


Jose Unpingco - Python for Probability, Statistics, and Machine Learning (EPUB)

Python for Probability, Statistics, and Machine Learning by Jose Unpingco
English | 28 Mar. 2016 | ISBN: 3319307150 | 294 Pages | EPUB | 4.91 MB
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads.



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Learning Deep Architectures for AI (Foundations and Trends(r) in Machine Learning)


Learning Deep Architectures for AI (Foundations and Trends(r) in Machine Learning)

Learning Deep Architectures for AI (Foundations and Trends(r) in Machine Learning) by Yoshua Bengio
English | Oct. 28, 2009 | ISBN: 1601982941 | 130 Pages | PDF | 1 MB
Can machine learning deliver AI? Theoretical results, inspiration from the brain and cognition, as well as machine learning experiments suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one would need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers, graphical models with many levels of latent variables, or in complicated propositional formulae re-using many sub-formulae.



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An Introduction to Machine Learning with Web Data

An Introduction to Machine Learning with Web Data

An Introduction to Machine Learning with Web Data
HDRips | MP4/AVC, ~1200 kb/s | 1280x720 | Duration: 02:43:22 | English: AAC, 128 kb/s (2 ch) | 1.43 GB
Genre: Development / Programming

Once you've accumulated a pile of data through your web application, what do you do with it? In this insightful video course, bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. You'll follow several examples through the entire process-from obtaining, cleaning, and exploring data to building a model and interpreting the results.

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Python: Real World Machine Learning

Python: Real World Machine Learning

Python: Real World Machine Learning by Prateek Joshi
English | 14 Nov. 2016 | ASIN: B01N74UY6B | ISBN-13: 9781787123212 | 983 Pages | MOBI/EPUB/PDF | 53.2 MB

Learn to solve challenging data science problems by building powerful machine learning models using Python.

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An Introduction to Machine Learning with Web Data

An Introduction to Machine Learning with Web Data

An Introduction to Machine Learning with Web Data
HDRips | MP4/AVC, ~1200 kb/s | 1280x720 | Duration: 02:43:22 | English: AAC, 128 kb/s (2 ch) | 1.43 GB
Genre: Development / Programming
Once youve accumulated a pile of data through your web application, what do you do with it? In this insightful video course, bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. Youll follow several examples through the entire process-from obtaining, cleaning, and exploring data to building a model and interpreting the results.


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An Introduction to Machine Learning with Web Data [repost]

An Introduction to Machine Learning with Web Data [repost]
An Introduction to Machine Learning with Web Data
HDRips | MP4/AVC, ~1200 kb/s | 1280x720 | Duration: 02:43:22 | English: AAC, 128 kb/s (2 ch) | 1.43 GB
Genre: Development / Programming
Once youve accumulated a pile of data through your web application, what do you do with it? In this insightful video course, bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. Youll follow several examples through the entire process-from obtaining, cleaning, and exploring data to building a model and interpreting the results.




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Classification Using Tree Based Models

Classification Using Tree Based Models
Classification Using Tree Based Models
Duration: 1h 56m | Video: h264, yuv420p 1280x720 | Audio: aac, 44100 Hz, 2 ch | 239 MB
Genre: eLearning | Language: English | Project Files


Machine Learning can sound very complicated, but anyone with a will to learn can successfully apply it, if they approach it from first principles. This course, Classification Using Tree Based Models, covers a specific class of Machine Learning problems - classification problems and how to solve these problems using Tree based models. First, you'll learn about building and visualizing decision trees as well as recognizing the serious problem of overfitting and its causes. Next, you'll learn about using ensemble learning to overcome overfitting. Finally, you'll explore 2 specific ensemble learning techniques - Random Forests and Gradient boosted trees By the end of this course, you'll be able to recognize opportunities where you can use Tree based models to solve classification problems and measure how well your solution is doing.

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Unsupervised Deep Learning in Python

Unsupervised Deep Learning in Python

Unsupervised Deep Learning in Python: Master Data Science and Machine Learning with Modern Neural Networks written in Python and Theano (Machine Learning in Python) by LazyProgrammer
English | 30 Jun 2016 | ASIN: B01HUA6BOG | 62 Pages | AZW3/MOBI/EPUB/PDF (conv) | 1.26 MB

When we talk about modern deep learning, we are often not talking about vanilla neural networks - but newer developments, like using Autoencoders and Restricted Boltzmann Machines to do unsupervised pre-training.

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Learning Path Scaling Python for Big Data

Learning Path Scaling Python for Big Data
Learning Path: Scaling Python for Big Data
HDRips | MP4/AVC, ~73 kb/s | 1280x720 | Duration: 07:03:02 | English: AAC, 128 kb/s (2 ch) | 1,52 GB
Genre: Development / Programming
If you have some Python experience, and you want to take it to the next level, this practical, hands-on Learning Path will be a helpful resource. Video tutorials in this Learning Path will show you how to use Python for distributed task processing, perform large-scale data processing in Spark using the PySpark API, and tackle machine learning tasks with Python.




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Introduction To Data Science

Introduction To Data Science

Introduction To Data Science
WEBRip | English | MP4 | 1280 x 720 | AVC ~936 kbps | 30 fps
AAC | 61.9 Kbps | 44.1 KHz | 2 channels | 05:52:02 | 2.39 GB
Genre: eLearning Video / Business, Data Analysis

Use the R Programming Language to execute data science projects and become a data scientist. Implement business solutions, using machine learning and predictive analytics. The R language provides a way to tackle day-to-day data science tasks, and this course will teach you how to apply the R programming language and useful statistical techniques to everyday business situations. With this course, you'll be able to use the visualizations, statistical models, and data manipulation tools that modern data scientists rely upon daily to recognize trends and suggest courses of action.

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Getting Started with Natural Language Processing with Python (2016)

Getting Started with Natural Language Processing with Python (2016)

Getting Started with Natural Language Processing with Python
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hours 43M | 240 MB
Genre: eLearning | Language: English

This course is all about taking raw text data and deriving insights and value from it-processing text data using standard techniques in Natural Language Processing and Machine Learning.

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Getting Started with Natural Language Processing with Python (2016)

Getting Started with Natural Language Processing with Python (2016)

Getting Started with Natural Language Processing with Python
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hours 43M | 240 MB
Genre: eLearning | Language: English

This course is all about taking raw text data and deriving insights and value from it-processing text data using standard techniques in Natural Language Processing and Machine Learning.

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Introduction to Data Analytics with KNIME

Introduction to Data Analytics with KNIME

Introduction to Data Analytics with KNIME
HDRips | MP4/AVC, ~562 kb/s | 1280x720 | Duration: 03:01:32 | English: AAC, 128 kb/s (2 ch) | 892 MB
Genre: Data Analytics

This is a hands-on basic course about data analytics and KNIME, and is designed for learners with little experience in data analytics or in programming. Taught by 24 year data analytics veteran Dr. Rosaria Silipo, it covers everything a beginning data analyst needs to know. You'll learn about importing data from common data sources and how to investigate data using visual exploration, ETL, data blending, and some machine learning algorithms.

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