Cancer Genomics | Neural Networks vs k-NN Classifiers
Cancer Genomics | Neural Networks vs k-NN Classifiers, available at Free, has an average rating of 4.4, with 7 lectures, based on 53 reviews, and has 1281 subscribers.
You will learn about Use Anaconda IDE Use Jupyter IDE Machine Learning Cancer Genomics k-NN Classifier Neural Networks Deep Learning mglearn Library for Visualization This course is ideal for individuals who are Aspired Data Scientist or Python Programmers interested in Cancer Genomics It is particularly useful for Aspired Data Scientist or Python Programmers interested in Cancer Genomics.
Enroll now: Cancer Genomics | Neural Networks vs k-NN Classifiers
Summary
Title: Cancer Genomics | Neural Networks vs k-NN Classifiers
Price: Free
Average Rating: 4.4
Number of Lectures: 7
Number of Published Lectures: 7
Number of Curriculum Items: 7
Number of Published Curriculum Objects: 7
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
- Use Anaconda IDE
- Use Jupyter IDE
- Machine Learning
- Cancer Genomics
- k-NN Classifier
- Neural Networks
- Deep Learning
- mglearn Library for Visualization
Who Should Attend
- Aspired Data Scientist
- Python Programmers interested in Cancer Genomics
Target Audiences
- Aspired Data Scientist
- Python Programmers interested in Cancer Genomics
Cancer Genomics | Neural Networks vs k-NN Classifiers : Machine Learning for Python Hackers is a crash course in Data Science and Cancer Genomics for anyone interested in cancer research. The course starts out with loading up a cancer dataset to split train and test. This course is unique in Data Science in that it uses the mglearn library for better visualization and is dedicated to providing details as such so the student can follow along with no ambiguity.
- k-NN Classifications with detailed visualization
- Neural Network built from scratch with line by line explanation and visualization!
- Build a GC :Content Calculator!
Course Curriculum
Chapter 1: Introduction to Cancer Genomics
Lecture 1: Introduction
Chapter 2: KNN CLASSIFIERS
Lecture 1: k-NN Classification 1
Lecture 2: k-NN Classification 2
Chapter 3: NEURAL NETWORKS
Lecture 1: Neural Nets Part 1
Lecture 2: Neural Nets Part 2
Chapter 4: CANCER GENOMICS
Lecture 1: Hacking Cancer DNA: 1 of 2
Lecture 2: Hacking Cancer DNA: 2 | Guanine/Cytosine : Ratio, (G/C:Counts)
Instructors
-
Brian Rouse
Data Scientist / iOS Instructor
Rating Distribution
- 1 stars: 7 votes
- 2 stars: 6 votes
- 3 stars: 13 votes
- 4 stars: 11 votes
- 5 stars: 16 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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