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<!DOCTYPE html>
<html>
<head>
<link rel="icon" href="images/ml_logo.png">
<meta HTTP-EQUIV="REFRESH" content="0; url=https://e2eml.school/blog.html">
<meta charset='utf-8'>
<meta http-equiv="X-UA-Compatible" content="chrome=1">
<meta name="description" content="Brandon Rohrer: e2eML Library">
<link rel="stylesheet" type="text/css" href="stylesheets/stylesheet.css" media="screen">
<link rel="stylesheet" type="text/css" href="stylesheets/print.css" media="print">
<base target="_blank">
<title>Library for End-to-End Machine Learning</title>
</head>
<body>
<!-- HEADER -->
<div id="header_wrap" class="outer">
<header class="inner">
<h1 id="project_title">
End-to-End Machine Learning Library
</h1>
</header>
</div>
<!-- MAIN CONTENT -->
<div id="main_content_wrap" class="outer">
<section id="main_content" class="inner">
<p>
Welcome!
Pour yourself a mug of something hot and have a look around.
</p>
<p>
If you're wondering where to get started, here are some
<a href="https://end-to-end-machine-learning.teachable.com/blog/196278/recommended-course-sequences">
recommended course sequences</a>. Whether you are new to
data science or want to dive into
building your own neural networks, there is a set of courses
lined up for you.
</p>
<hr>
<h4>300 series. Project courses with coding.</h4>
<table>
<tr>
<td>
<h4>September 1, 2020</h4>
</td>
<td>
<h3>316. Recurrent Neural Networks</h3>
<!--
<ul>
<li>
</li>
<li>
</li>
</ul>
-->
</td>
</tr>
<tr>
<td>
<h4>June 1, 2020</h4>
</td>
<td>
<h3>315. Convolutional Neural Networks</h3>
<!--
<ul>
<li>
</li>
<li>
</li>
</ul>
-->
</td>
</tr>
<tr>
<td>
<a href="
https://end-to-end-machine-learning.teachable.com/p/314-neural-network-optimization/
">
<img src="images/course_314_thumbnail.png"
alt="neural network optimization course" style="height: 153px;">
</a>
</td>
<td>
<a href="
https://end-to-end-machine-learning.teachable.com/p/314-neural-network-optimization/
">
<h3>314. Neural Network Optimization</h3>
</a>
<ul>
<li>
Build an autoencoder to extract basis elements of images
of the Martian surface.
</li>
<li>
Optimize compression performance by tuning hyperparameters.
</li>
<li>
Build and use
<a href="https://e2eml.school/evopowell.html">
Evolutionary Powell's method</a>,
an experimental hyperparameter optimization algorithm.
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/advanced-neural-network-methods/">
<img src="images/thumbnail_mars_autoencoder.png"
alt="advanced neural network methods course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/advanced-neural-network-methods/">
<h3>313. Advanced Neural Network Methods</h3>
</a>
<ul>
<li>
Add regularization, dropout, computation graphs
and optimizer options to the framework
we built in Course 312.
</li>
<li>
<a href="https://github.com/brohrer/cottonwood_martian_images">
Run it on images from Mars.</a>
</li>
<li>
<a href="
https://e2eml.school/regularization.html
">How Regularization Works</a>
</li>
<li>
<a href="
https://end-to-end-machine-learning.teachable.com/courses/advanced-neural-network-methods/lectures/12194418
">What is a Computation Graph?</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/write-a-neural-network-framework">
<img src="images/thumbnail_neural_network_framework.png"
alt="neural network visualization course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/write-a-neural-network-framework">
<h3>312. Build a Neural Network Framework</h3></a>
<ul>
<li>
Code up a fully connected deep neural network from scratch in Python.
</li>
<li>
Extend it into a framework through object-oriented design.
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/neural-network-visualization/">
<img src="images/neural_network_visualization.png"
alt="neural network visualization course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/neural-network-visualization/">
<h3>311. Neural Network Visualization</h3></a>
<ul>
<li>
Create a custom neural network visualization in python.
</li>
<li>
Learn Matplotlib tricks for making professional plots.
</li>
</ul>
</td>
</tr>
</table>
<h4>200 series. Application-centered case studies. </h2>
<table>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/polynomial-regression-optimization/">
<img src="images/thumbnail_polynomial_regression.png"
alt="polynomial regression course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/polynomial-regression-optimization/">
<h3>213. Polynomial Regression</h3>
<ul>
<li>
Code up a robust optimizer from scratch in python.
</li>
<li>
Fit high-order polynomials to real data on dog breeds.
</li>
<li>
Implement Monte Carlo cross-validation to select the best model.
</li>
</ul>
</a>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/time-series-analysis-weather-predictor/
">
<img src="images/thumbnail_time_series.png"
alt="time-series course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/time-series-analysis-weather-predictor/
">
<h3>212. Time-series Prediction</h3>
<ul>
<li>
Build a command line weather prediction tool from a century of data.
</li>
<li>
Perform data-driven deseasonalization to remove annual
weather patterns.
</li>
<li>
Use autocorrelation to extract predicted temperatures.
</li>
</ul>
</a>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/decision-trees-with-python-and-pandas/">
<img src="images/thumbnail_decision_trees.png"
alt="decision trees course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/decision-trees-with-python-and-pandas/">
<h3>211. Decision Trees</h3>
<ul>
<li>
Code up a decision tree in python from scratch.
</li>
<li>
Dynamically construct URL queries for live transit data API.
</li>
<li>
Use Pandas DataFrames to model transit time distributions.
</li>
<li>
Build the model into a command line application.
</li>
</ul>
</a>
</td>
</tr>
</table>
<h4>100 series. Foundational concepts and skills.</h4>
<p>
Everything below this line is free.
</p>
<table>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/how-deep-neural-networks-work/">
<img src="images/thumbnail_how_nns_work.png"
alt="how neural networks work course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/how-deep-neural-networks-work/">
<h3>193. How Neural Networks Work</h3></a>
<ul>
<li>
<a href="how_neural_networks_work.html">
How fully connected neural networks work
</a>
</li>
<li>
<a href="what_nns_learn.html">
What neural networks can learn
</a>
</li>
<li>
<a href="how_backpropagation_works.html">
How backpropagation works
</a>
</li>
<li>
<a href="how_convolutional_neural_networks_work.html">
How convolutional neural networks work
</a>
</li>
<li>
<a href="how_rnns_lstm_work.html">
How recurrent neural networks and LSTM work
</a>
</li>
<li>
<a href="deep_learning_demystified.html">
How deep learning works
</a>
</li>
<li>
<a href="https://youtu.be/0ILdnZmp3Iw">
Getting closer to human intelligence through robotics
</a>
</li>
<li>
<a href="https://youtu.be/JB8T_zN7ZC0">
How convolutional neural networks work, in depth
</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/machine-learning-signal-processing-statistics-concepts/">
<img src="images/thumbnail_how_stuff_works.png"
alt="how stuff works course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/machine-learning-signal-processing-statistics-concepts/">
<h3>191. How Selected Models and Methods Work</h3></a>
<ul>
<li>
<a href="how_decision_trees_work.html">
How decision trees work
</a>
</li>
<li>
<a href="how_bayesian_inference_works.html">
How Bayesian inference works
</a>
</li>
<li>
<a href="https://youtu.be/ZjaBn93YPWo">
How autocorrelation works
</a>
</li>
<li>
<a href="open_the_black_box.html">
How support vector machines work
</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/building-blocks-how-optimization-works/">
<img src="images/thumbnail_how_optimization_works.png"
alt="how optimization works course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/building-blocks-how-optimization-works/">
<h3>173. How Optimization for Machine Learning Works</h3></a>
<ul>
<li>
<a href="how_optimization_works_1.html">Optimization methods</a>
</li>
<li>
<a href="how_optimization_works_2.html">Optimizing a central tendency model</a>
</li>
<li>
<a href="how_optimization_works_3.html">Optimizing a linear model</a>
</li>
<li>
<a href="how_optimization_works_4.html">Optimizing complex models</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/building-blocks-choosing-a-model/">
<img src="images/thumbnail_how_choose_model.png"
alt="model selection course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/building-blocks-choosing-a-model/">
<h3>171. How to Choose a Model</h3></a>
<ul>
<li>
<a href="how_modeling_works_1.html">Choosing between models</a>
</li>
<li>
<a href="how_modeling_works_2.html">Separating signal from noise</a>
</li>
<li>
<a href="how_modeling_works_3.html">Choosing a loss function</a>
</li>
<li>
<a href="how_modeling_works_4.html">Splitting the data</a>
</li>
<li>
<a href="how_modeling_works_5.html">Navigating assumptions</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/navigating-matplotlib-tutorial-how-to/">
<img
src="https://github.com/brohrer/taming_matplotlib/raw/master/images/thumbnail_matplotlib_just_plot_it.png"
alt="matplotlib course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/navigating-matplotlib-tutorial-how-to/">
<h3>133. How to Navigate Matplotlib</h3></a>
<ul>
<li>
<a href="matplotlib_just_plot_it.html">
Make your first plots
</a>
</li>
<li>
<a href="matplotlib_going_deeper.html">
Figures and Axes
</a>
</li>
<li>
<a href="matplotlib_lines.html">
Lines and curves
</a>
</li>
<li>
<a href="matplotlib_points.html">
Scatterplots and points
</a>
</li>
<li>
<a href="matplotlib_text.html">
Text, axis labels, and annotation
</a>
</li>
<li>
<a href="matplotlib_ticks.html">
Ticks, tick labels, and grids
</a>
</li>
<li>
<a href="matplotlib_framing.html">
Layout, background, and multiple plots
</a>
</li>
<li>
<a href="matplotlib_resources.html">
Resources
</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/data-munging-tips-and-tricks/">
<img src="images/thumbnail_data_munging.png"
alt="data munging course" style="height: 153px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/data-munging-tips-and-tricks/">
<h3>131. Data Munging Tips and Tricks</h3></a>
<ul>
<li>
<a href="dataframe_indexing.html">
How to slice and index pandas DataFrames
</a>
</li>
<li>
<a href="https://e2eml.school/data_files.html">
Reading and writing data files
</a>
</li>
<li>
<a href="
https://e2eml.school/personal_toolbox.html
">
Create a personal Python toolbox
</a>
</li>
<li>
<a href="
https://e2eml.school/code_optimization.html
">
Make your code run faster
</a>
</li>
<li>
<a href="
https://e2eml.school/multiprocessing.html
">
Run your code on several cores at once
</a>
</li>
<li>
<a href="datetime_tricks.html">
How to use datetime
</a>
</li>
<li>
<a href="images_to_numbers.html">
How to turn a picture into numbers
</a>
</li>
<li>
<a href="convert_rgb_to_grayscale.html">
How to convert RGB color images to grayscale
</a>
</li>
<li>
<a href="images_to_video.html">
How to convert images to video and back
</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/navigating-a-data-science-career/">
<img src="images/zen_stones.jpg"
alt="data science career advice" style="height: 173px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/navigating-a-data-science-career/">
<h3>121. Navigating a data science career</h3></a>
<ul>
<li>
<a href="data_science_archetypes.html">
Data science archetypes
</a>
</li>
<li>
<a href=" professional_path.html ">
Planning your professional path
</a>
</li>
<li>
<a href="how_to_interview.html">
How to navigate a data science interview
</a>
</li>
<li>
<a href="one_step_program_become_data_scientist.html">
How to become a data scientist
</a>
</li>
<li>
<a href="get_data_science_job.html">
How to get hired as a data scientist
</a>
</li>
<li>
<a href="https://datamovesme.com/courses/up-level-your-resume/">
Up-level your resume
</a>
</li>
<li>
<a href="influencing.html">
Get people to listen to you on the Internet
</a>
</li>
<li>
<a href="stop_chasing_unicorns.html">
How to build a data science team
</a>
</li>
<li>
<a href="distributed_data_science_team.html">
How to make a great remote data science team
</a>
</li>
<li>
<a href="which_tool_should_i_use.html">
How to choose your tools
</a>
</li>
<li>
<a href="oversimplify.html">
Oversimplify
</a>
</li>
<li>
<a href="imposter_syndrome.html">
Imposter syndrome
</a>
</li>
<li>
<a href="org_response.html">
Responding to leaders' misbehavior
</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/data-science-concepts/">
<img src="images/how_to_do_data_science.png"
alt="data science concepts" style="height: 193px;">
</a>
</td>
<td>
<a href="https://end-to-end-machine-learning.teachable.com/p/data-science-concepts/">
<h3>101. Data science concepts</h3></a>
<ul>
<li>
<a href="pocket_guide_data_science.html">
How data science works
</a>
</li>
<li>
<a href="https://azure.microsoft.com/en-us/documentation/articles/machine-learning-data-science-for-beginners-the-5-questions-data-science-answers/">
Data science for beginners
</a>
</li>
<li>
<a href="data_science_other_stuff.html">
There is more to data science than machine learning
</a>
</li>
<li>
<a href="https://youtu.be/tKa0zDDDaQk?t=40s">
What is data
</a>
</li>
<li>
<a href="make_data_science_work_for_you.html">
How to get good quality data
</a>
</li>
<li>
<a href="five_questions_data_science_answers.html">
What questions can machine learning answer
</a>
</li>
</ul>
</td>
</tr>
<tr>
<td>
<img src="images/waterfall.png" style="height: 193px;">
</td>
<td>
<h3>
<a href="
https://end-to-end-machine-learning.teachable.com/p/000-foundational-skills/">
Foundational Skills</a>
<a id="skills"></a></h3></a>
<ul>
<li>
<a href="mindfulness_reading_list.html">
091. Mental Focus
</a>
</li>
<li>
<a href="git_resources.html">
071. Git
</a>
</li>
<li>
<a href="stats_resources.html">
041. Statistics
</a>
</li>
<li>
<a href="linear_algebra_resources.html">
032. Linear Algebra
</a>
</li>
<li>
<a href="calculus_resources.html">
031. Calculus
</a>
</li>
<li>
<a href="sql_resources.html">
021. SQL
</a>
</li>
<li>
<a href="cpp_resources.html">
016. C++
</a>
</li>
<li>
<a href="numpy_resources.html">
012. NumPy
</a>
</li>
<li>
<a href="python_resources.html">
011. Python
</a>
</li>
</ul>
</td>
</tr>
</table>
<br>
</section>
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