Let’s face it – Machine Learning is everywhere in our world today.
From self-driving cars, credit card fraud detection, automatic image captioning, recommendation systems, image classification, financial trading, machine translation, and even for blockchain to detect anomalous behaviour anywhere along the chain.
Machine Learning has become a key component of the modern software technology landscape. One reason for this is that we live in a more and more interconnected world that generates a great amount of information every day. Data is really the key factor today and the main driver for this data growth is for sure the internet. It is impossible for us humans to analyze the data because it’s just too much and it keeps growing. On top of this, computational power and data storage becomes cheaper and more powerful.
We are entering the era where computers are extremely powerful and can process things way faster than we can imagine, and this is what’s mainly facilitating machine learning or rather deep learning.
Working with machine learning is not only very impactful, but also interesting and creative!
If you want to learn more about Machine Learning and why it's such a powerful tool, this course is exactly right for you.
This course covers the most important topics to get you up and running with easy to follow videos and a handful of practical exercises.
The first chapter is available now, and you can watch all videos from this chapter for free! If you like them, why don't you preorder the course and get access to all future chapters.
You can find the free chapter in our class curriculum!
Obviously we’ll talk a lot about Machine Learning, but specifically about what it is and why we need it. We are gonna compare machine learning to good-old fashioned AI (traditional rule-based approaches) and we’ll see that these rule-based systems are quite limiting in certain uses cases, such as image classification, and often provide unsatisfactory results or become very error-prone.
We'll learn what Machine Learning is all about. In particular, we will look at neural networks and by building one from scratch in 20 lines of vanilla Python, we shed some light on the inner workings and uncover the “magic” that is powering these beasts.
From here, we will move on to a deep learning library called Keras and by solving some real world problems we will explore its API.
In addition, we learn about different types of machine learning as well as see various types of neural networks in action.
By the end of this course I hope that you ll be left with an intuition for how to approach problems using machine learning and a familiarity with implementing machine learning algorithms yourself.
This course is for...
Hey! My name is Dominic Elm and I am a Software Engineer, Trainer at thoughtram and Co-Founder of MachineLabs.
My mission with this course is to make Machine Learning more accessible and less scary for all of us.
We will publish more chapters as they are finished. Remember, this course is currently available for preorder.
If you decide to preorder the course, your credit card will only be charged when the EAP officially starts (Q2 2019).
Learn what Machine Learning is all about. We'll find out how to solve a Machine Learning task in 20 lines of pure Python.
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 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 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 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.
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!
All you need is some basic, beginner-level experience with Python.
You don’t need to know anything about Machine Learning – everything is covered in the course.
High school level math skills will be helpful but are not mandatory.
|We are committed to create the most beginner friendly Machine Learning course available. We are confident you'll get everything you need from this course and be 100% satisfied. But in the unlikely event you decide this course is not for your, you can ask for a refund any time during the first 30 days. We will make sure you’ll get your money back with no questions asked.|