Unlock the power of deep learning and elevate your machine learning skills with our comprehensive deep neural networks course. This hands-on program covers deep learning fundamentals, including artificial neural networks, activation functions, bias, data, and loss functions. Learn Python basics focused on data science, and master tools like Matplotlib, NumPy, and Pandas for data cleaning and visualization. Progress from the MP Neuron model to the Perceptron, Sigmoid Neuron, and Universal Approximation Theorem, exploring ReLU and SoftMax activation functions. Gain practical experience with TensorFlow 2.x, creating and training deep neural networks, evaluating their performance, and fine-tuning for optimal results. By the course's end, you'll be on your way to becoming a deep-learning expert. This beginner-friendly course is perfect for students and professionals aiming to stay updated on AI. A basic understanding of programming is recommended but not required, as foundational Python skills are covered in the course.
Summary on Activation Functions
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Skills You'll Learn
Deep Learning, TensorFlow, Data Science, Machine Learning, Artificial Intelligence
From the lesson
Activation Functions in Deep Learning Neural Networks
In this module, we will cover activation functions in deep learning. You will learn about different activation functions provided by TensorFlow and understand common network configurations used in deep learning tasks.
Taught By
Packt - Course Instructors