Python and TensorFlow Data Science and Iris Speciation
Python and TensorFlow Data Science and Iris Speciation, available at $49.99, has an average rating of 4.5, with 106 lectures, based on 5 reviews, and has 88 subscribers.
You will learn about 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! This course is ideal for individuals who are Anyone who needs to learn classification or Anyone who needs to learn Python or Anyone who needs to graph with Python or Anyone who needs to know more about machine learning or Anyone who wants to use efficient arrays or Anyone who needs an efficient way to analyze data or Anyone with little to no knowledge of machine learning or Anyone with little to no programming experience or Anyone with no Python experience It is particularly useful for Anyone who needs to learn classification or Anyone who needs to learn Python or Anyone who needs to graph with Python or Anyone who needs to know more about machine learning or Anyone who wants to use efficient arrays or Anyone who needs an efficient way to analyze data or Anyone with little to no knowledge of machine learning or Anyone with little to no programming experience or Anyone with no Python experience.
Enroll now: Python and TensorFlow Data Science and Iris Speciation
Summary
Title: Python and TensorFlow Data Science and Iris Speciation
Price: $49.99
Average Rating: 4.5
Number of Lectures: 106
Number of Published Lectures: 106
Number of Curriculum Items: 106
Number of Published Curriculum Objects: 106
Original Price: $199.99
Quality Status: approved
Status: Live
What 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!
Who Should Attend
- 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
Target Audiences
- 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
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:
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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.
Course Curriculum
Chapter 1: Python Language Basics
Lecture 1: Python Language Basics Introduction
Lecture 2: Intro to Python
Lecture 3: Variables
Lecture 4: Type Conversion Examples
Lecture 5: Operators
Lecture 6: Operators Examples
Lecture 7: Collections
Lecture 8: Lists
Lecture 9: Multidimensional List Examples
Lecture 10: Tuples Examples
Lecture 11: Dictionaries Examples
Lecture 12: Ranges Examples
Lecture 13: Conditionials
Lecture 14: If Statements Examples
Lecture 15: if Statements Variants Examples
Lecture 16: Loops
Lecture 17: While Loops Examples
Lecture 18: For Loops Examples
Lecture 19: Functions
Lecture 20: Functions Examples
Lecture 21: Parameters And Return Values Examples
Lecture 22: Classes and Objects
Lecture 23: Classes Examples
Lecture 24: Objects Examples
Lecture 25: Inheritance Examples
Lecture 26: Static Members Examples
Lecture 27: Summary and Outro
Lecture 28: Intro to Python PDF Resource
Lecture 29: Source Code ($150 Value)
Chapter 2: NumPy Course
Lecture 1: NumPy Course Introduction
Lecture 2: Introduction to NumPy
Lecture 3: Installing NumPy
Lecture 4: Creating NumPy Arrays
Lecture 5: Creating NumPy Matrices
Lecture 6: Getting and Setting NumPy Elements
Lecture 7: Arithmetic Operations on NumPy Arrays
Lecture 8: NumPy Functions Part 1
Lecture 9: NumPy Functions Part 2
Lecture 10: Summary and Outro
Lecture 11: Source Code ($150 Value)
Lecture 12: Numpy PDF Resource
Chapter 3: Pandas Course
Lecture 1: Panda Course Introduction
Lecture 2: Introduction to Pandas
Lecture 3: Installing Pandas
Lecture 4: Creating Pandas Series
Lecture 5: Date Ranges
Lecture 6: Getting Elements from Series
Lecture 7: Getting Properties of Series
Lecture 8: Modifying Series
Lecture 9: Operations on Series
Lecture 10: Creating Pandas DataFrames
Lecture 11: Getting Elements from DataFrames
Lecture 12: Getting Properties from DataFrames
Lecture 13: Dataframe Modification
Lecture 14: DataFrame Operations
Lecture 15: DataFrame Comparisons and Iteration
Lecture 16: Reading CSVs
Lecture 17: Summary and Outro
Lecture 18: Pandas PDF Resource
Lecture 19: Source Code ($150 Value)
Chapter 4: PyPlot Course
Lecture 1: PyPlot Course Introduction
Lecture 2: Introduction to PyPlot
Lecture 3: Installing Matplotlib
Lecture 4: Basic Line Plot
Lecture 5: Customizing Graphs
Lecture 6: Plotting Multiple Datasets
Lecture 7: Bar Chart
Lecture 8: Pie Chart
Lecture 9: Histogram
Lecture 10: 3D Plotting
Lecture 11: Course Outro
Lecture 12: Source Code ($150 Value)
Chapter 5: Machine Learning Course
Lecture 1: Machine Learning Course Introduction
Lecture 2: Introduction to Machine Learning
Lecture 3: Deep Dive into Machine Learning
Lecture 4: Problems Solved with Machine Learning Part 1
Lecture 5: Problems Solved with Machine Learning Part 2
Lecture 6: Types of Machine Learning
Lecture 7: How Machine Learning Works
Lecture 8: Common Machine Learning Structures
Lecture 9: Steps to Build a Machine Learning Program
Lecture 10: Summary and Outro
Lecture 11: Intro to Machine Learning PDF Resource
Chapter 6: TensorFlow Course
Lecture 1: TensorFlow Course Introduction
Lecture 2: Introduction to Tensorflow
Lecture 3: Installing Tensorflow
Lecture 4: Intro to Linear Regression
Lecture 5: Linear Regression Model – Creating Dataset
Lecture 6: Linear Regression Model – Building the Model
Lecture 7: Linear Regression Model – Creating a Loss Function
Lecture 8: Linear Regression Model – Training the Model
Lecture 9: Linear Regression Model – Testing the Model
Lecture 10: Summary and Outro
Lecture 11: Intro to Tensorflow PDF Resource
Instructors
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Mammoth Interactive
Top-Rated Instructor, 3.3 Million+ Students -
John Bura
Best Selling Instructor Web/App/Game Developer 1Mil Students
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 1 votes
- 4 stars: 1 votes
- 5 stars: 3 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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