| Description |
1 online resource (1 video file (6 hr., 28 min.)) : sound, color. |
| Playing Time |
062800 |
| Description |
digital rdatr |
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video file rdaft |
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Instructional films lcgft |
| Performer |
AI Sciences, presenter. |
| Note |
"Published in January 2023." |
| Summary |
Are you ready to start your path to becoming a deep learning expert? Then this course is for you. This course is step-by-step. In every new tutorial, we build on what we have already learned and move one extra step forward, and then we assign you a small task that is solved at the beginning of the next video. We start by teaching the theoretical part of the concept, and then implement everything as it is practically using Python. This comprehensive course will be your guide to learning how to use the power of Python to train your machine such that your machine starts learning just like humans, and based on that learning, your machine starts making predictions as well! We will be using Python as a programming language in this course, which is the hottest language nowadays if we talk about machine learning. Python will be taught from the elementary level up to an advanced level so that any machine learning concept can be implemented. You will also learn various steps of data preprocessing, which allows us to make data ready for machine learning algorithms. You will learn the general concepts of machine learning overall, which will be followed by the implementation of one of the essential ML algorithms, "Deep Neural Networks". Each concept of DNNs will be taught theoretically and will be implemented using Python. By the end of this course, you will be able to understand the methodology of DNNs with deep learning using real-world datasets. What You Will Learn Learn the basics of machine learning and neural networks Understand the architecture of neural networks Learn the basics of training a DNN using the Gradient Descent algorithm Learn how to implement a complete DNN using NumPy Learn to create a complete structure for DNN from scratch using Python Work on a project using deep learning for the IRIS dataset Audience This course is designed for anyone who is interested in data science or interested in taking their data-speak to a higher level. Students who want to master DNNs with real datasets in deep learning or who want to implement DNNs in realistic projects can also benefit from the course. You need to have a background in deep learning to get the best out of this course. About The Author AI Sciences: AI Sciences is a group of experts, PhDs, and practitioners of AI, ML, computer science, and statistics. Some of the experts work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. They have produced a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science. Initially, their objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory. Today, they also publish more complete courses for a wider audience. Their courses have had phenomenal success and have helped more than 100,000 students master AI and data science. |
| Subject |
Deep learning (Machine learning)
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Neural networks (Computer science)
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Python (Computer program language)
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Computer programming.
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Apprentissage profond. |
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Réseaux neuronaux (Informatique) |
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Python (Langage de programmation) |
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Programmation (Informatique) |
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computer programming. |
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Computer programming |
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Deep learning (Machine learning) |
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Neural networks (Computer science) |
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Python (Computer program language) |
| Genre |
Instructional films
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Internet videos
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Nonfiction films
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Instructional films.
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Nonfiction films.
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Internet videos.
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Films de formation.
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Films autres que de fiction.
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Vidéos sur Internet.
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| Added Author |
AI Sciences (Firm), presenter.
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Packt Publishing, publisher.
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| ISBN |
9781837633579 (electronic video) |
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1837633576 (electronic video) |
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