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

Ratings: 4.35 / 5.00




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.

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