What you would learn in Deep Learning Fundamentals | Theory & Practice with Python course?
Python is one of the most effective programming languages because of its flexibility. It can be used in all areas, including web development, to develop financial applications. It's not a secret that the most effective application of Python is deep learning and artificial intelligence tasks.
Although Python allows deep learning to be simple, however, it can be very frustrating for a person not aware of the way machine learning operates in the first place.
If you're familiar with the basics of Python and want to pursue deeper learning, then this class has been made specifically for you. This course will assist you in developing programs that use data input and automate feature extraction, making it easier for humans to perform real-world tasks.
There is a myriad of machine learning resources through the web. But, you're in danger of absorbing unnecessary lessons when you don't filter the information you're learning. When we've created this program, we've assisted by filtering the information to identify the fundamentals you'll need during your journey of deep learning.
It's a fundamentals class that is suitable for beginners and experts. If you're searching for a class that begins and builds towards more advanced subjects, it's the ideal option for you.
It teaches only the basics needed to get started with deep learning and no gimmicks. While this keeps the lesson short, It's all you require to begin in the field.
Who should this course be intended for:
Programmers looking to deepen their arsenal of skills
Professional mathematicians eager to master the art of analyzing data in a programming manner
Anyone Python programmer who is looking to add deep-learning expertise to their existing portfolio
Content of the Course:
Learn the basics of the theory of Deep Learning theory
Learn to utilize Deep Learning in Python
Learn to apply various frameworks available in Python to tackle real-world issues with Artificial Intelligence and Deep Learning
Create predictions using Polynomial regression and linear regression, and multivariate regression
Create artificial neural networks using Tensorflow and Keras
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