Make predictions with Python machine learning for apps

About Make predictions with Python machine learning for apps

Go through 3 _ultimate_ levels of artificial intelligence for beginners!

Learn artificial intelligence, machine learning, and mobile dev with Java, Android, TensorFlow Estimator, PyCharm, and MNIST. Woah! That's a lot of content for one course.

This course was funded by a wildly successful Kickstarter

Use Google's deep learning framework TensorFlow with Python. Leverage machine learning to improve your apps

Prediction Models Masterclass

By the end of this course you will have 3 complete mobile machine learning models and apps. We will build a simple

_weather prediction_

project,

_stock market prediction_

project, and

_text-response_

project. For each we will build a basic version in PyCharm, save the trained model, export the trained model to Android Studio, and build an app around model.

No experience? No problem

We'll give you all necessary information to succeed from newbie to pro. We will install PyCharm 2017.2.3 and explore the interface. I will show you every step of the way. You will learn

_crucial_

Python 3.6.2 language fundamentals. Even if you have coding knowledge, going back to the basics is the

_key_

to success as a programmer. We will build and run Python projects. I teach through _practical examples_ , follow-alongs, and over-the-shoulder tutorials.

_You won't need to go anywhere else._

Then we will install Android Studio 3 and explore the interface. You will learn how to add a simulator and build simple User Interfaces (UIs). For coding, you will learn Java 8 language fundamentals. Java is a

_HUGE_

language that you must know, and I will tell you all about it. We will build and run Android projects directly in the course, and you will have

_solid examples_

to _apply your knowledge_ immediately.

Complete Image Recognition and Machine Learning for Beginners

With this course I will help you understand what machine learning is and compare it to Artificial Intelligence (AI). Together we will discover applications of machine learning and where we use machine learning daily. Machine learning, neural networks, deep learning, and artificial intelligence are all around us, and _they're not going away_. I will show you how to get a grasp on this ever-growing technology in this course. We will explore different machine learning mechanisms and commonly used algorithms. These are popular and ones you should know. Next I'll teach you what TensorFlow 1.4.1 is and how it makes machine learning development easier. You will learn how to install TensorFlow and access its libraries through PyCharm. You'll understand the basic components of TensorFlow. Follow along with me to build a

_complete computational model_

. We'll train and test a model and use it for future predictions. I'll also show you how to build a

_linear regression model_

to fit a line through data. You'll learn to train and test the model, evaluate model accuracy, and predict values using the model.

Stock Market, Weather & Text - Let's Go!