Udemy – ANNs and DNNs 0 to 100 | Python | Machine Learning | AI 2024-8

Published on: 2024-09-15 16:00:48

Categories: 28

Description

Course of ANNs and DNNs 0 to 100 | Python | Machine learning AI. This comprehensive course will take you on an exciting journey to master Artificial Neural Networks (ANNs) and Deep Neural Networks (DNNs). This course, specially designed for beginners and those looking to increase their knowledge, offers a combination of theoretical concepts and practical exercises of coding in Python. In this course, you will learn the basics of neural networks and gradually move towards more advanced concepts. From linear classification to complex neural networks, you’ll learn everything step-by-step.

What you will learn in this course:

Linear Classification: Understanding the basics of classification algorithms and their role in machine learning.
Support Vector Machines (SVM): Introduction to SVM, powerful supervised learning models used for classification and regression.
Overfitting and Overfitting: Learn how to identify overfitting in your models and overfitting techniques to avoid it.
Softmax: mastering the Softmax function for multi-class classification problems.
Gradient Descent: Understanding the Optimization Method Essential for Training Neural Networks.
Backpropagation: Gaining insight into an algorithm that adjusts weights in a network to minimize error.
Deep neural networks (DNNs): exploring advanced architectures and how they can significantly improve model performance.
Dropout: Implementation of dropout techniques to avoid overfitting in deep learning models.
Convolutional Neural Networks (CNNs): An in-depth review of CNNs for image processing and other applications.

This course is suitable for people who:

They are looking for career advancement in any field.
They want to increase their knowledge in the field of machine learning and artificial intelligence.
Looking to solve complex machine learning challenges with confidence.