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Python and TensorFlow Data Science and Iris Speciation

Master Machine Learning, PyPlot, NumPy, Pandas, Data Science, Iris Speciation with TensorFlow & Land a High Paying Job
4.4
4.4/5
(5 reviews)
81 students
Created by

8.8

CourseMarks Score®

7.5

Freshness

8.2

Feedback

10.0

Content

Platform: Udemy
Video: 16h 30m
Language: English
Next start: On Demand

Top Artificial Intelligence courses:

Detailed Analysis

CourseMarks Score®

8.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

7.5 / 10
This course was last updated on 4/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.2 / 10
We analyzed factors such as the rating (4.4/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

10.0 / 10
Video Score: 10.0 / 10
The course includes 16h 30m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 5 hours 26 minutes of 212 Artificial Intelligence courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

12 articles.
12 resources.
0 exercise.
0 test.

Table of contents

Description

Machine learning allows you to build more powerful, more accurate and more user friendly software that can better respond and adapt.
Many companies are integrating machine learning or have already done so, including the biggest Google, Facebook, Netflix, and Amazon.
There are many high paying machine learning jobs.
Jump into this fun and exciting course to land your next interesting and high paying job with the projects you’ll build and problems you’ll learn how to solve.
In just a matter of hours you’ll have new skills with projects to back them up: 
•Deep dive into machine learning
•Problems that machine learning solves
•Types of machine learning
•Common machine learning structures
•Steps to building a machine learning model
•Build a linear regression machine learning model with TensorFlow
•Test and train the model
•Python variables and operators
•Collection types
•Conditionals and loops
•Functions
•Classes and objects
•Install and import NumPy
•Build NumPy arrays
•Multidimensional NumPy arrays
•Array indexes and properties
•NumPy functions
•NumPy operations
•And much more!
Add new skills to your resume in this project based course:
•Graph data with PyPlot
•Customize graphs
•Build 3D graphs with PyPlot
•Use TensorFlow to build a program to categorize irises into different species.
•Build a classification model
•Track data
•Implement logic
•Implement responsiveness
•Build data structures
•Replace Python lists with NumPy arrays
•Build and use NumPy arrays
•Use common array functions
•Use Pandas series
•Use Pandas Date Ranges
•Use Pandas DataFrames
•Read CSVs with Pandas
•Install and import Pandas
•Build Pandas Series and DataFrames
•Get elements from a Series
•Get properties from a series
•Modify series
•Series operations
•Series comparisons and iteration
•And much more!
Machine learning is quickly becoming a required skill for every software developer.
Enroll now to learn everything you need to know to get up to speed, whether you’re a developer or aspiring data scientist. This is the course for you.
Your complete Python course for image recognition, data analysis, data visualization and more.
Reviews On Our Python Courses:
•”I know enough Python to be dangerous. Most of the ML classes are so abstract and theoretical that no learning happens. This is the first class where we use concrete examples that I can relate to and allow me to learn. Absolutely love this course!” – Mary T.

•”Yes, this is an amazing start. For someone new in python this is a very simple boot course. I am able to relate to my earlier programming experience with ease!” – Gajendran C.

•”Clear and concise information” – Paul B.

•”Easy to understand and very clear explanations. So far so good!!!” – Alejandro M.
All source code is included for each project.
Don’t miss out! Sign up to join the community.

You will learn

✓ Graph data with PyPlot
✓ Build 3D graphs with PyPlot
✓ Customize graphs
✓ Use TensorFlow to build a program to categorize irises into different species.
✓ Build a classification model
✓ Implement logic
✓ Track data
✓ Implement responsiveness
✓ Replace Python lists with NumPy arrays
✓ Build data structures
✓ Build and use NumPy arrays
✓ Use Pandas series
✓ Use common array functions
✓ Use Pandas Date Ranges
✓ Read CSVs with Pandas
✓ Use Pandas DataFrames
✓ Get elements from a Series
✓ Get properties from a series
✓ Series operations
✓ Modify series
✓ Series comparisons and iteration
✓ Series operations
✓ And much more!

Requirements

• No experience necessary
• No OS requirement but the tutorials are recorded on a Mac with Google Colab

This course is for

• Anyone who needs to learn classification
• Anyone who needs to learn Python
• Anyone who needs to graph with Python
• Anyone who needs to know more about machine learning
• Anyone who wants to use efficient arrays
• Anyone who needs an efficient way to analyze data
• Anyone with little to no knowledge of machine learning
• Anyone with little to no programming experience
• Anyone with no Python experience

How much does the Python and TensorFlow Data Science and Iris Speciation course cost? Is it worth it?

The course costs $14.99. And currently there is a 82% discount on the original price of the course, which was $109.99. So you save $95 if you enroll the course now.
The average price is $18.0 of 212 Artificial Intelligence courses. So this course is 17% cheaper than the average Artificial Intelligence course on Udemy.

Does the Python and TensorFlow Data Science and Iris Speciation course have a money back guarantee or refund policy?

YES, Python and TensorFlow Data Science and Iris Speciation has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Python and TensorFlow Data Science and Iris Speciation course, but there is a $95 discount from the original price ($109.99). So the current price is just $14.99.

Who is the instructor? Is Mammoth Interactive a SCAM or a TRUSTED instructor?

Mammoth Interactive has created 217 courses that got 11,646 reviews which are generally positive. Mammoth Interactive has taught 371,655 students and received a 4.3 average review out of 11,646 reviews. Depending on the information available, Mammoth Interactive is a TRUSTED instructor.
Top-Rated Instructor, 800,000+ Students
“I absolutely love this course. This is such a comprehensive course that was well worth the money I spent and a lot more. Will definitely be looking at more Mammoth Interactive courses when I finish this.” – Student Matt W.
“Very good at explaining the basics then building to more complex features.” – Student Kevin L.
Mammoth Interactive has been contracted to produce epic soundtracks, addicting levels, rock solid programming and business development.
Browse all courses by on Coursemarks.

8.8

CourseMarks Score®

7.5

Freshness

8.2

Feedback

10.0

Content

Platform: Udemy
Video: 16h 30m
Language: English
Next start: On Demand

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