Machine Learning Jump Start


The most practical Machine Learning online course

FEATURES

BEGINNER FRIENDLY

Are you tired of Machine Learning courses that start with linear algebra?

We've been so tired with courses that preach a Math-first approach that we set out to build the most beginner friendly Machine Learning course in the world.

This course is for coders and tinkerers! We take a very code-centered, practical approach to Machine Learning.

ZERO SETUP

We've built MachineLabs to make Machine Learning radically simple.

This course leverages the power of the MachineLabs platform so you can dive right in to the exciting stuff without any hassle of configuring software or GPU drivers.

You'll be using leading Machine Learning frameworks such as Keras and TensorFlow.

VIDEOS

Before we let you solve challenges in interactive labs, we'll explain concepts in detailed, easy to follow videos.

Stream or download. Learn at home or on the daily commute.

INTERACTIVE LABS

Each lesson comes with interactive labs to solve.

These labs run on the MachineLabs platform, have access to state-of-the-art Machine Learning tools & datasets and run on GPU-enabled hardware.

GET HELP FROM PEERS & EXPERTS

Get members-only exclusive access to our slack channel where participants can come together to push and help each other.

We'll also be running a couple of AMA-styled expert hours to answer open questions.

TOPICS

PREORDER
Early Access Preview starting in April 2018
Introduction

Learn what Machine Learning is all about. We'll find out how to solve a Machine Learning task in 20 lines of pure Python.

ML Fundamentals

ReLU, Max Pooling and Dropouts scare you? There's a whole lot of intimidating vocabulary in Machine Learning. We introduce enough of each concept at the right point in time.

Keras API

Keras is a framework that uses TensorFlow behind the scenes and describes itself as being designed for human beings, not machines. We'll explore all important APIs together.

Convolutional Networks

Convolutional Networks are great for image recognition but can be used to process all kind of spatial data. We'll take a deep dive into CNN architecture to demystify the concept and apply it to real world challenges.

Recurrent Networks

Recurrent Neural Networks (RNNs) are popular models and a powerful tool for many Natural Language Processing (NLP) tasks. In this course we'll dive into RNNs and apply them to some common NLP tasks, such as machine translations.

Reinforcement Learning

Somewhere in between supervised and unsupervised learning, RL is one of the most exciting fields of Machine Learning that exists today. We'll build an AI together that beats you at your favourite game!

Preorder without any risk

We are commited to create the most beginner friendly Machine Learning course available

You won't get charged before the Early Access Preview begins.

100 % refund policy: if you're not satisfied for any reason, reach out to us via email and we'll give you a full refund.

Preorder-exclusive deals
  • Up to 70 % off from the regular price
  • Early Access Preview starting in April 2018
  • 20 free GPU hours every month for one year

PRICING

Preorder now before the price goes up

Machine Learning Jump Start (Single License)

89

299 70% off
days left
  • Free GPU hours
  • Early Access Preview
  • Free lifetime updates
  • Private Slack community

WHO'S BEHIND THIS?

We are the same people that run thoughtram. We've trained thousands of people, from individual developers to governments.

Christoph Burgdorf

Software gardener. Thinks the world is a blockchain.

Pascal Precht

Likes synthesizers, art and coding. Google Developer Expert

Dominic Elm

Sportsman. Instructor at thoughtram.

Newsletter

Receive updates about this course. We don't spam.