Deep Learning with TensorFlow: Applications of Deep Neural Networks to Machine Learning Tasks

LeeAndro · May 22, 2022

Video: .MP4, 1280x720 30 fps | Audio: AAC, 48kHz, 2ch | Duration: 6h
Genre: eLearning | Language: English + Subtitles | Size: 9.98 GB

Deep Learning with TensorFlow LiveLessons is an introduction to Deep Learning that bring the revolutionary machine-learning approach to life with interactive demos from the most popular Deep Learning library, TensorFlow, and its high-level API, Keras.

Essential theory is whiteboarded to provide an intuitive understanding of Deep Learning's underlying foundations, i.e., artificial neural networks. Paired with tips for overcoming common pitfalls and hands-on code run-throughs provided in Python-based Jupyter notebooks, this foundational knowledge empowers individuals with no previous understanding of neural networks to build powerful state-of-the-art Deep Learning models.
The companion materials for this LiveLesson can be found at
Skill Level
Intermediate
Learn How To
Build Deep Learning models in TensorFlow and Keras
Interpret the results of Deep Learning models
Troubleshoot and improve Deep Learning models
Understand the language and fundamentals of artificial neural networks
Build your own Deep Learning project
Who Should Take This Course
This course is perfectly suited to software engineers, data scientists, analysts, and statisticians with an interest in Deep Learning. Code examples are provided in Python, so familiarity with it or another object-oriented programming language would be helpful. Previous experience with statistics or machine learning is not necessary.
Course Requirements
Some experience with any of the following are an asset, but none are essential:
Object-oriented programming, specifically Python
Simple shell commands, e.g., in Bash
Machine learning or statistics
First-year college calculus

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Deep Learning with TensorFlow: Applications of Deep Neural Networks to Machine Learning Tasks

LeeAndro

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