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CBTNuggets - Introduction to Deep Learning - Panter - 02.09.2024
![[Bild: dbd994759283303a8412c3010ab2d85e.jpg]](https://i123.fastpic.org/big/2024/0902/5e/dbd994759283303a8412c3010ab2d85e.jpg)
CBTNuggets - Introduction to Deep Learning
Released 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 280 Lessons ( 30h 43m ) | Size: 20.4 GB
This deep learning training equips junior data scientists with the expertise needed to implement deep learning solutions for their organization's specific needs. Building on the principles of machine learning, this course provides an introduction to deep learning, focusing on image data using computer vision (CV), text data using natural language processing (NLP), and time-series data for predictive modeling.
This course will not only teach you how to use TensorFlow for image and text classification, it will also help you gain an understanding of Large Language Models (LLMs).
For anyone with junior data scientists on their team, this data science training can be used to onboard new junior data scientists, curated into individual or team training plans, or as a data science reference resource.
After completing this deep learning training, you'll know how to describe deep learning methods and techniques well enough to begin implementing deep learning solutions for your organization's unique needs.
Introduction to Deep Learning: What You Need to Know
This deep learning training has videos that cover topics including
Building and training neural networks for image and text classification
Learning the differences between machine learning and deep learning, and when to use one over the other
Understanding Convolutional Neural Networks (CNNs) and Natural Language Processing (NLP) techniques
Evaluating and optimizing deep learning models using pre-trained models from TensorFlow, Google, and Kaggle
Who Should Take Introduction to Deep Learning Training?
This deep learning training is considered associate-level data science training, which means it was designed for data scientists who have a basic understanding of Python programming and machine learning concepts, including supervised and unsupervised learning.
New or aspiring junior data scientists. If you're a brand new data scientist, this deep learning course can be used to start your career off on the right foot. Gain hands-on experience with deep learning and learn valuable skills you can use to solve complex problems in image and text analysis.
Experienced junior data scientists. Data scientists with a few years of experience have likely encountered deep learning tools or implementations. You may have even struggled through them on your own. This deep learning training will help you bring more value to your organization by augmenting your skills in Convolutional Neural Networks (CNNs) and Natural Language Processing (NLP) for computer vision tasks and text classification analysis.
![[Bild: 509029245_introduction_to_deep_learning.jpg]](https://img99.pixhost.to/images/240/509029245_introduction_to_deep_learning.jpg)
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