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Otomatic
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Re: error during the installation

[WOW] Deep Learning Prerequisites: Linear Regression in Python

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		1. Deep Learning Prerequisites: Linear Regression in Python.zip
		2. ReadMe.Important!.txt
		3. Changelog.txt
		4. Documentation.html
		5. Deep Learning Prerequisites: Linear Regression in Python Update.zip
		

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		SHA256:	ac1cb9b991508bafc3be40d15f1572fde9d905841f621115d243c2f1374ff98b
		File name:	Deep Learning Prerequisites: Linear Regression in Python.rar
		Detection ratio:	0 / 53 / Clean 
		Analysis date:	25.04.2015 17:44 UTC
		

Description


		

This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own linear regression module in Python.

Linear regression is the simplest machine learning model you can learn, yet there is so much depth that youll be returning to it for years to come. Thats why its a great introductory course if youre interested in taking your first steps in the fields of:

  • deep learning
  • machine learning
  • data science
  • statistics

In the first section, I will show you how to use 1-D linear regression to prove that Moores Law is true.

Whats that you say? Moores Law is not linear?

You are correct! I will show you how linear regression can still be applied.

In the next section, we will extend 1-D linear regression to any-dimensional linear regression - in other words, how to create a machine learning model that can learn from multiple inputs.

We will apply multi-dimensional linear regression to predicting a patients systolic blood pressure given their age and weight.

Finally, we will discuss some practical machine learning issues that you want to be mindful of when you perform data analysis, such as generalization, overfitting, train-test splits,�and so on.

This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for FREE.

If you are a programmer and you want to enhance your coding abilities by learning about data science, then this course is for you. If you have a technical or mathematical background, and you want to know how to apply your skills as a software engineer or hacker, this course may be useful.

This course focuses on how to build and understand, not just how to use. Anyone can learn to use an API in 15 minutes after reading some documentation. Its not about remembering facts, its about�seeing for yourself via experimentation. It will teach you how to visualize whats happening in the model internally. If you want�more�than just a superficial look at machine learning models, this course is for you.


NOTES:

All the code for this course can be downloaded from my github: /lazyprogrammer/machine_learning_examples

In the directory: linear_regression_class

Make sure you always git pull so you have the latest version!


HARD PREREQUISITES /�KNOWLEDGE�YOU�ARE ASSUMED�TO�HAVE:

  • calculus
  • linear algebra
  • probability
  • Python coding: if/else, loops, lists, dicts, sets
  • Numpy coding: matrix and vector operations, loading a CSV file


TIPS (for getting through the course):

  • Watch it at 2x.
  • Ask lots of questions on the discussion board. The more the better!
  • Realize that most exercises will take you days or weeks to complete.


USEFUL�COURSE�ORDERING:

  • (The Numpy Stack in Python)
  • Linear Regression in Python
  • Logistic Regression in Python
  • (Supervised Machine Learning in Python)
  • Deep Learning in Python
  • Practical Deep Learning in Theano and TensorFlow
  • Convolutional Neural Networks in Python
  • (Easy NLP)
  • (Cluster Analysis and Unsupervised Machine Learning)
  • Unsupervised Deep Learning
  • (Hidden Markov Models)
  • Recurrent Neural Networks in Python
  • Natural Language Processing with�Deep Learning in Python


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14.11.2016 02:11

Wepid1998
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+5 Rep Given. Much appreciated


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19.11.2016 21:55

Antemblowind2002
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Deep Learning Prerequisites: Linear Regression in Python -

Thanks +REP


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29.11.2016 14:34

Sood2001
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Deep Learning Prerequisites: Linear Regression in Python -

Wow, way to go. Thanks for sharing, reps added.


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30.11.2016 09:16

Thimply
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Thanks you very much... rep +5.


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03.12.2016 01:14

Spoed1997
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Thanks once again. PM'd and +5 repped.


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09.12.2016 21:12

Douner
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Deep Learning Prerequisites: Linear Regression in Python -

Awesome share you rock!


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10.12.2016 12:28

Finiz2001
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Deep Learning Prerequisites: Linear Regression in Python -

OMG thanks!!! Rep +++++


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16.12.2016 22:46

Mung1996
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Thank you very much. Maximum Rep +5 added.


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23.12.2016 12:57

Asom1994
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Deep Learning Prerequisites: Linear Regression in Python -

Thanks for sharing


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24.12.2016 14:38

Parloo
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Deep Learning Prerequisites: Linear Regression in Python -

Thank you for your time and efforts to help other members. +5 Rep added


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28.12.2016 22:29

Leopull84
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Deep Learning Prerequisites: Linear Regression in Python -

Thanks for the great share


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02.01.2017 13:49

Driblen1985
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Deep Learning Prerequisites: Linear Regression in Python -

great share, rep up


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07.01.2017 16:51

Firear
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Deep Learning Prerequisites: Linear Regression in Python -

All Mega links still working perfectly. Max reps added for your kindness :)


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14.01.2017 02:17

Scablevoled
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Deep Learning Prerequisites: Linear Regression in Python -

thanks for share man, I really want this.


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