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 (AI) tasks.
You’ll start with an introduction to deep learning where you’ll focus on the fundamentals of the deep learning theory and find out how to use deep learning in Python, before moving on to artificial neural networks (ANNs). You’ll learn how to use different frameworks in Python to solve real-world problems using deep learning and artificial intelligence. Next, you’ll discover how to make predictions using linear regression, polynomial regression, and multivariate regression, and build artificial neural networks with TensorFlow and Keras. The video also covers convolutional neural networks (CNNs) at length and goes through the different components such as convolution layer, pooling layer, and fully connected layer. Finally, you’ll wrap up CNN implementation in Python.
By the end of this course, you’ll be able to use the concepts of deep learning to build neural networks in Python like a professional.
publication date
2022-08-24
what you will learn
Get to grips with the fundamentals of the deep learning theory
Discover how to use deep learning in Python
Find out how to use different frameworks in Python
Build artificial neural networks with TensorFlow and Keras
Explore the implementation of ANNs and CNNs in Python
key features
Fundamentals course designed for both beginners and experts alike * Use different frameworks in Python to solve real-world problems using deep learning and AI * Make predictions using linear regression, polynomial regression, and multivariate regression
approach
This fundamentals training is excellent for both newcomers and seasoned professionals. This is the best course for you if you're looking for one that starts with the fundamentals and progresses to more complex subjects. It does not teach anything but what is necessary to get started with deep learning. This is pretty much everything you need to get started with the topic, and it also helps to keep the course quite concise.
audience
This course is for both programming beginners and professionals who want to expand on their knowledge of deep learning, or professional mathematicians looking to learn how to analyze data programmatically. Prerequisites include basic mathematical skills and Python coding experience.
short description
This comprehensive deep learning course with Python will start with the basics and work up to advanced topics such as using different frameworks in Python to solve real-world problems and building artificial neural networks with TensorFlow and Keras.
subtitle
Master data science, TensorFlow, artificial intelligence, and neural networks
keywords
Artificial Intelligence, Data science, Neural Networks, TensorFlow, Convolutional Neural Networks, Artificial Neural Networks, Neural Network Architectures, Activation Functions, Gradient Descent Algorithm
Product ISBN
9781804617878
