English | Size: 656.03 MB
Genre: eLearning
What you’ll learn
Learn the fundamentals of the Deep Learning theory
Learn how to use Deep Learning in Python
Learn how to use different frameworks in Python to solve real-world problems using deep learning and artificial intelligence
Make predictions using linear regression, polynomial regression, and multivariate regression
Build artificial neural networks with Tensorflow and Keras
Python is famed as one of the best programming languages for its flexibility. It works in almost all fields, from web development to developing financial applications. However, it’s no secret that Python’s best application is in deep learning and artificial intelligence tasks.
While Python makes deep learning easy, it will still be quite frustrating for someone with no knowledge of how machine learning works in the first place.
If you know the basics of Python and you have a drive for deep learning, this course is designed for you. This course will help you learn how to create programs that take data input and automate feature extraction, simplifying real-world tasks for humans.
There are hundreds of machine learning resources available on the internet. However, you’re at risk of learning unnecessary lessons if you don’t filter what you learn. While creating this course, we’ve helped with filtering to isolate the essential basics you’ll need in your deep learning journey.
It is a fundamentals course that’s great for both beginners and experts alike. If you’re on the lookout for a course that starts from the basics and works up to the advanced topics, this is the best course for you.
It only teaches what you need to get started in deep learning with no fluff. While this helps to keep the course pretty concise, it’s about everything you need to get started with the topic.
Who this course is for:
Programmers who are looking to add deep learning to their skillset
Professional mathematicians willing to learn how to analyze data programmatically
Any Python programming enthusiast willing to add deep learning proficiency to their portfolio
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