[vc_column_text]R is now considered one of the most popular analytics tools in the world. This Machine Learning with R mini bootcamp dives into the basics of machine learning using this approachable, and well-known, programming language. During this mini bootcamp, You’ll learn about Supervised vs Unsupervised Learning, and you will also look into Dimensionality Reduction & Collaborative Filtering.<\/p>\n
<\/p>\n
This mini bootcamp also provides you to look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!<\/p>\n
<\/p>\n
Who is this course for:<\/p>\n
<\/p>\n
\u25cf <\/span>Anyone who wants an introduction to Machine Learning with R.
\n\u25cf <\/span>Anyone who is interested in building ML applications in R.<\/p>\n <\/p>\n
Course Requirements:<\/p>\n
<\/p>\n
\u25cf <\/span>Need to know theory of ML.
\n\u25cf <\/span>Basic Math knowledge.[\/vc_column_text]<\/div>[vc_column_text]
What will you learn?<\/strong><\/p>\n <\/p>\n
\u25cf Module 1 – Machine Learning vs Statistical Modeling & Supervised vs Unsupervised Learning
\n\u25cf Machine Learning Languages, Types, and Examples
\n\u25cf Machine Learning vs Statistical Modelling
\n\u25cf Supervised vs Unsupervised Learning
\n\u25cf Supervised Learning Classification
\n\u25cf Unsupervised Learning<\/span><\/p>\n <\/p>\n
\u25cf Module 2 – Supervised Learning I
\n\u25cf K-Nearest Neighbors
\n\u25cf Decision Trees
\n\u25cf Random Forests
\n\u25cf Reliability of Random Forests
\n\u25cf Advantages & Disadvantages of Decision Trees<\/p>\n
\n\u25cf Module 3 – Supervised Learning II
\n\u25cf Regression Algorithms
\n\u25cf Model Evaluation
\n\u25cf Model Evaluation: Overfitting & Underfitting
\n\u25cf Understanding Different Evaluation Models<\/span><\/p>\n
\n\u25cf Module 4 – Unsupervised Learning
\n\u25cf K-Means Clustering plus Advantages & Disadvantages
\n\u25cf Hierarchical Clustering plus Advantages & Disadvantages
\n\u25cf Measuring the Distances Between Clusters – Single Linkage Clustering
\n\u25cf Measuring the Distances Between Clusters – Algorithms for Hierarchy Clustering
\n\u25cf Density-Based Clustering<\/span><\/p>\n
\n\u25cf Module 5 – Dimensionality Reduction & Collaborative Filtering
\n\u25cf Dimensionality Reduction: Feature Extraction & Selection
\n\u25cf Collaborative Filtering & Its Challenges <\/span>[\/vc_column_text]<\/div>[vc_column_text]Start learning the R with Machine Learning with outside of business hours schedule!<\/p>\n
The 12 hours of schedule is as follows:<\/p>\n
<\/p>\n
March 14 \u2013 21 \u2013 28 and April 4
\nSaturdays, from 2:00 pm to 5:00 pm[\/vc_column_text]<\/div>
[vc_column_text]The venue for the bootcamp is Magnimind Academy Sunnyvale Campus: 830 Stewart Dr #182, Sunnyvale, CA 94085. The capacity is limited to 20 people.[\/vc_column_text]<\/div>
[vc_column_text]Machine Learning with R Mini Bootcamp is now also available online. Anyone who wants to attend this mini bootcamp can join online live webinars where the same course content will be taught. Online sessions will be distributed through zoom conferences. Students will have access to the screen of the instructor, external camera showing class atmosphere, whiteboard, and be able to ask questions through chat. You may attend this mini bootcamp no matter where you are.[\/vc_column_text]<\/div>
[vc_column_text]
Tuition fee<\/b><\/p>\n <\/p>\n
Machine Learning with R Mini Bootcamp has a $300 tuition fee.
\nFor the \u201cEarly Bird\u201d applicants (January 15<\/span> \u2013 March 7), the tuition fee is $250.<\/span><\/p>\n <\/p>\n
Payment process<\/b><\/p>\n
<\/p>\n
After you finish filling your application form, the website will direct you to the payment page. There, you can select available payment options.<\/p>\n
<\/p>\n
Cancellation<\/b><\/p>\n
<\/p>\n
If you\u2019re not satisfied with the course you may cancel your application.\u00a0<\/span>[\/vc_column_text]<\/div>[vc_column_text]
Course Application<\/b><\/p>\n <\/p>\n
The application process starts at magnimindacademy.com. You can view the course pages and learn more about your intended course. You can apply by clicking the \u201cBuy now\u201d button and then fill out the application form.[\/vc_column_text]<\/div>
[vc_column_text]Mr. Clem Wang has been a Data Scientist for 15 years, working at both large companies like Yahoo and Microsoft, and a bunch of startups. He’s used both Python and R professionally. In a previous life, he’s been involved with QA’ing compilers and interpreters, so he has some insights in the inner workings of R and Python.[\/vc_column_text]<\/div><\/div>[\/vc_column][\/vc_row]\n<\/div>","protected":false},"excerpt":{"rendered":"
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