Category: Machine Learning

Introduction to Numpy, Pandas, Matplotlib
Download Jupyter Notebook file -> CAP4

Introduction to Numpy, Pandas, Matplotlib
Download Jupyter Notebook file -> CAP4611-HW1-Tools.ipynbDownload CAP4611-HW1-Tools.ipynb
Follow the prompts in the attached Jupyter Notebook. Download the data from (Modules/ Datasets for Assignment) and place it in your working directory, or modify the path to upload it to your notebook.
Before every code cell, add markdown cells to your analysis. Include your solutions, comments, and answers on how to solve the problem. Add as many cells as you need, for easy readability comments when possible.
Hopefully, this homework will provide you with an introduction on the tools you need to use to learn about Machine Learning and get you ready for individual work.
Submission: Save your ipynb file named with your Name_HW1 (e.g.John_Doe_HW1.ipynb).
Good luck!

INSTRUCTIONS
Every learner should submit his/her own homework solutions. However

INSTRUCTIONS
Every learner should submit his/her own homework solutions. However, you are allowed to discuss the homework with each other– but everyone must submit his/her own solution; you may not copy someone else’s solution.
The homework helps you understand and apply K Nearest Neighbor.
Follow the prompts in the attached Jupyter notebook. CAP4611-HW3-NearestNeighbors.ipynbDownload CAP4611-HW3-NearestNeighbors.ipynb
Download the data from (Modules/ Data for Homework Assignment) and place it in your working directory, or modify the path to upload it to your notebook.
Before every code cell, add markdown cells to your analysis. Include your solutions, comments, and answers on how to solve the problem. Add as many cells as you need, for easy readability comments when possible.
Hopefully this homework will help you develop skills, make you understand how K nearest neighbor works.
Submission: Save your ipynb file named with your Name_HW3 (e.g.John_Doe_HW3.ipynb).
Good luck!

one page reading response on the book:
[Deep Feedforward Networks
link:
https:/

one page reading response on the book:
[Deep Feedforward Networks
link:
https://www.deeplearningbook.org/contents/mlp.htmlYou can summarize, or focus and explain the part(s) that you enjoyed reading more in detail. You’re allowed a maximum of one page. No outside resources. Use first person point of view. Also use diagrams, graphs or equation to summarize. If you could use latex that will be great

INSTRUCTIONS
Every learner should submit his/her own homework solutions. However

INSTRUCTIONS
Every learner should submit his/her own homework solutions. However, you are allowed to discuss the homework with each other– but everyone must submit his/her own solution; you may not copy someone else’s solution.
The homework helps you understand and apply K Nearest Neighbor.
Follow the prompts in the attached Jupyter notebook. CAP4611-HW3-NearestNeighbors.ipynbDownload CAP4611-HW3-NearestNeighbors.ipynb
Download the data from (Modules/ Data for Homework Assignment) and place it in your working directory, or modify the path to upload it to your notebook.
Before every code cell, add markdown cells to your analysis. Include your solutions, comments, and answers on how to solve the problem. Add as many cells as you need, for easy readability comments when possible.
Hopefully this homework will help you develop skills, make you understand how K nearest neighbor works.
Submission: Save your ipynb file named with your Name_HW3 (e.g.John_Doe_HW3.ipynb).
Good luck!

one page reading response on the book:
[Murphy, Book 1, Chapter 12.1-12.3]
You c

one page reading response on the book:
[Murphy, Book 1, Chapter 12.1-12.3]
You can summarize, or focus and explain the part(s) that you enjoyed reading more in detail. You’re allowed a maximum of one page. No outside resources. Use first person point of view.

one page reading response on the book:
[Murphy, Book 1, Chapter 12.1-12.3]
You c

one page reading response on the book:
[Murphy, Book 1, Chapter 12.1-12.3]
You can summarize, or focus and explain the part(s) that you enjoyed reading more in detail. You’re allowed a maximum of one page. No outside resources. Use first person point of view.