What Is Keras? | What Is Keras In Deep Learning | Keras Tutorial For Beginners | Simplilearn
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AI Summary of "What Is Keras? | What Is Keras In Deep Learning | Keras Tutorial For Beginners | Simplilearn"
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Artificial Intelligence and Neural Networks Overview
📌 The video aims to explain Artificial Intelligence (AI), focusing on Deep Learning, and how it works through Neural Networks.
🧠 Deep Learning involves building and executing complex models, often utilizing Machine Learning algorithms across multiple layers to extract high-level features.
⚙️ Convolutional Neural Networks (CNNs) are highlighted as a popular type used to extract features from unstructured data like images.
Neural Network Fundamentals
🌐 A Neural Network is inspired by the biological concept of neurons, where multiple interconnected neurons are required to solve complex problems.
📊 Basic models like the Perceptron use techniques like multiple linear regression and activation functions within hidden layers for input weighting.
💻 Modern computational systems, including mobile devices and various computing resources, are essential for running and implementing these powerful AI models.
Model Training and Implementation
🛠️ A typical five-step pipeline for a Neural Network includes: feeding the network with training data, validating performance using testing data, and ensuring the entire process runs smoothly across CPUs and GPUs.
🚀 Distributed training is a crucial technique where Deep Learning models are split across different parts of a system globally, making training extremely fast and leveraging vast computational power.
✅ Neural Networks are designed for human ease of use, following best practices to minimize required user input and maximize user feedback integration for better performance.
Key Points & Insights
➡️ Deep Learning relies on Machine Learning algorithms structured in multiple layers to process and understand complex data features.
➡️ Distributed training across various systems globally significantly accelerates model training time by utilizing collective computational resources.
➡️ Neural Network design prioritizes ease of learning and use for humans while focusing on developing productive and customizable AI solutions.
📸 Video summarized with SummaryTube.com on Nov 08, 2025, 10:03 UTC
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📜Transcript
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📄Video Description
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This video on What is Keras will help you understand the basics of a top deep learning library used in data science. You will learn the features of Keras, followed by how Keras performs operations. Finally, we'll look at the applications of Keras.
00:00:00 What is Deep Learning
00:03:34 What is Keras
00:06:33 Why Keras
00:07:41 Building a Model in Keras
00:08:38 Uses of Keras
✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH
⏩ Check out the Machine Learning tutorial videos: https://bit.ly/3fFR4f4
#WhatIsKeras #WhatIsKerasInDeepLearning #KerasTutorial #KerasTutorialForBeginners #WhatIsKerasInMachineLearning #ArtificialIntelligenceCourse #ArtificialIntelligenceTutorial #ArtificialIntelligenceTutorialForBeginners #Simplilearn
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This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.
IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.
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✅ Tools Covered
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Full video URL: youtube.com/watch?v=4Yy4ooOg69s
Duration: 19:00
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AI Summary of "What Is Keras? | What Is Keras In Deep Learning | Keras Tutorial For Beginners | Simplilearn"
Get instant insights and key takeaways from this YouTube video by Simplilearn.
Artificial Intelligence and Neural Networks Overview
📌 The video aims to explain Artificial Intelligence (AI), focusing on Deep Learning, and how it works through Neural Networks.
🧠 Deep Learning involves building and executing complex models, often utilizing Machine Learning algorithms across multiple layers to extract high-level features.
⚙️ Convolutional Neural Networks (CNNs) are highlighted as a popular type used to extract features from unstructured data like images.
Neural Network Fundamentals
🌐 A Neural Network is inspired by the biological concept of neurons, where multiple interconnected neurons are required to solve complex problems.
📊 Basic models like the Perceptron use techniques like multiple linear regression and activation functions within hidden layers for input weighting.
💻 Modern computational systems, including mobile devices and various computing resources, are essential for running and implementing these powerful AI models.
Model Training and Implementation
🛠️ A typical five-step pipeline for a Neural Network includes: feeding the network with training data, validating performance using testing data, and ensuring the entire process runs smoothly across CPUs and GPUs.
🚀 Distributed training is a crucial technique where Deep Learning models are split across different parts of a system globally, making training extremely fast and leveraging vast computational power.
✅ Neural Networks are designed for human ease of use, following best practices to minimize required user input and maximize user feedback integration for better performance.
Key Points & Insights
➡️ Deep Learning relies on Machine Learning algorithms structured in multiple layers to process and understand complex data features.
➡️ Distributed training across various systems globally significantly accelerates model training time by utilizing collective computational resources.
➡️ Neural Network design prioritizes ease of learning and use for humans while focusing on developing productive and customizable AI solutions.
📸 Video summarized with SummaryTube.com on Nov 08, 2025, 10:03 UTC
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As an Amazon Associate, we earn from qualifying purchases
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