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<!doctype html>
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<img
src="https://cognitiveclass.ai/wp-content/uploads/2016/10/Machine-Learning-with-Python.png">
</div>
<div class="course-info">
<h1 class="course-title">Machine Learning with Python</h1>
<p class="course-headline">Machine Learning can be an incredibly beneficial tool to uncover
hidden insights and predict future trends. This free Machine Learning with Python course
will give you all the tools you need to get started with supervised and unsupervised
learning.</p>
<a class="btn btn-primary btn-lg" href="https://cognitiveclass.ai/courses/machine-learning-with-python"
role="button">Enroll Now »</a>
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Machine Learning with Python
</a>
</li>
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<section class="course-content col-lg-9 col-lg-pull-3">
<h2>About this Course</h2>
<p>This Machine Learning with Python course dives into the basics of <em>Machine Learning</em>
using <em>Python</em>, an approachable and well-known programming language. You'll learn
about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to
Machine Learning, and do a comparison of each.<br>
Look at real-life examples of Machine Learning and how it affects society in ways you may
not have guessed!</p>
<p>Explore many algorithms and models:</p>
<ul>
<li>Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction.
</li>
<li>Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests.</li>
</ul>
<p>More important, you will transform your theoretical knowledge in to practical skill using
many hands-on labs.</p>
<p>Get ready to do more learning than your machine!</p>
<h2>Course Syllabus</h2>
<h5>Module 1 - Introduction to Machine Learning</h5>
<ul>
<li>Applications of Machine Learning</li>
<li>Supervised vs Unsupervised Learning</li>
<li>Python libraries suitable for Machine Learning</li>
</ul>
<h5>Module 2 - Regression</h5>
<ul>
<li>Linear Regression</li>
<li>Non-linear Regression</li>
<li>Model evaluation methods</li>
</ul>
<h5>Module 3 - Classification</h5>
<ul>
<li>K-Nearest Neighbour</li>
<li>Decision Trees</li>
<li>Logistic Regression</li>
<li>Support Vector Machines</li>
<li>Model Evaluation</li>
</ul>
<h5>Module 4 - Unsupervised Learning</h5>
<ul class="list-number1">
<li>K-Means Clustering</li>
<li>Hierarchical Clustering</li>
<li>Density-Based Clustering</li>
</ul>
<h5>Module 5 - Recommender Systems</h5>
<ul>
<li>Content-based recommender systems</li>
<li>Collaborative Filtering</li>
</ul>
<h2>Prerequisites for this course</h2>
<ul>
<li><a href="https://cognitiveclass.ai/courses/python-for-data-science/">Python for data
science</a></li>
</ul>
<h2>Recommended skills prior to taking this course</h2>
<ul>
<li>You have to do hands-on lab for this course. The tool that you use for hands-on is
called JupyterLab and it is one of the most popular tools used by data scientists. If
you are not familiar with JupyterLab, I would recommend that you take our free <a
href="https://cognitiveclass.ai/courses/data-science-hands-open-source-tools-2/"><span
class="s1">Data Science Hands-on with Open Source Tools</span></a>.</li>
<li>This hands-on lab requires that you have working knowledge of Python programming
language as it applies to data analytics. If you don't feel you have sufficient skill in
Data Analysis with Python, I recommend you take <a
href="https://cognitiveclass.ai/courses/data-analysis-python/">Data Analysis with
Python</a> courses.</li>
</ul>
<section class="course-staff">
<h3>Course Author</h3>
<p><a href="https://ca.linkedin.com/in/saeedaghabozorgi" target="_blank"
rel="noopener">Saeed Aghabozorgi</a>, PhD is a Sr. Data Scientist in IBM with a
track record of developing enterprise level applications that substantially increases
clients’ ability to turn data into actionable knowledge. He is a researcher in data
mining field and expert in developing advanced analytic methods like machine learning
and statistical modelling on large datasets.</p>
</section>
<section class="course-staff">
<h3>Other Contributors</h3>
<p>The following individual also contributed: <a
href="https://www.linkedin.com/in/agathacolangelo/">Agatha Colangelo</a></p>
</section>
<h1 class="pv-top-card-section__name Sans-26px-black-85%"></h1>
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