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Deep Learning with Keras and Tensorflow
Coursera
Course
Unknown

Deep Learning with Keras and Tensorflow

IBM

Master advanced deep learning techniques using Keras and TensorFlow to develop specialized models for computer vision, natural language processing, and reinforcement learning.

Unknown7 weeksEnglish

About this Course

Deep learning is revolutionizing many fields, including computer vision, natural language processing, and robotics. In addition, Keras, a high-level neural networks API written in Python, has become an essential part of TensorFlow, making deep learning accessible and straightforward. Mastering these techniques will open many opportunities in research and industry. You will learn to create custom layers and models in Keras and integrate Keras with TensorFlow 2.x for enhanced functionality. Y

What You'll Learn

  • Create custom layers and models in Keras and integrate with TensorFlow 2.x
  • Develop advanced convolutional neural networks using Keras
  • Build Transformer models for sequential data and time series prediction
  • Explain unsupervised learning, deep Q-networks (DQNs), and reinforcement learning concepts in Keras

Prerequisites

  • Basic Python programming knowledge
  • Fundamental machine learning concepts

Instructors

S

Samaya Madhavan

R

Ricky Shi

A

Alex Aklson

R

Romeo Kienzler

IBM Watson IoT

Topics

Generative Adversarial Networks (GANs)
Transfer Learning
Performance Tuning
Autoencoders
Tensorflow
Computer Vision
Keras (Neural Network Library)
Reinforcement Learning
Convolutional Neural Networks
Model Evaluation

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

الشبكات التوليدية الخصمية (GANs)
التعلم بالنقل
تحسين الأداء
المشفرات التلقائية
Tensorflow
الرؤية الحاسوبية
Keras (مكتبة الشبكات العصبية)
التعلم المعزز
Convolutional Neural Networks
Model Evaluation

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