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Deep Learning and Neural Networks in Python (Data Science) - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Deep Learning and Neural Networks in Python (Data Science) (/Thread-Deep-Learning-and-Neural-Networks-in-Python-Data-Science--503032) |
Deep Learning and Neural Networks in Python (Data Science) - OneDDL - 08-08-2024 ![]() Free Download Deep Learning and Neural Networks in Python (Data Science) Published 7/2024 Created by Chaitanya attaluri MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 32 Lectures ( 5h 43m ) | Size: 3.33 GB Learn to create Deep Learning models in Python What you'll learn: Deep Learning and Artificial Neural Networks Theory Types of Activation Functions Creating Artificail Neural Network (ANN)using Activation functions Tensof flow and keras Introduction Creating Convolutional Neural Network (CNN) using Teras flow and keras Creating Recurrent Neural Networks(RNN) Natural Language Processing(NLP) theory and Practice program Understanding about Computur Vision Assignment on ANN,CNN,RNN Requirements: Basic Python Programing Language Knowledge on Machine Learning models Description: This course introduces students to the theory and practice of deep learning, a subfield of machine learning that focuses on learning representations of data. Deep learning has gained significant attention and has achieved state-of-the-art results across various domains such as computer vision, natural language processing, and reinforcement learning. The course will cover foundational topics including neural networks, activation functions, optimization techniques, and regularization methods. Advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), Natural Language Processing(NLP),and computer vision will also be explored. Practical aspects of deep learning, including implementation using popular frameworks (e.g., TensorFlow, PyTorch) and the use of GPUs for acceleration, will be an integral part of the course. Real-world applications and case studies will be discussed to illustrate the power and potential of deep learning in solving complex problems. Throughout the course, students will gain hands-on experience through programming assignments where they will apply deep learning techniques to a challenging problem in their area of interest.Learning Objectives ![]() Who this course is for: Beginner on Deep Learning Homepage Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live No Password - Links are Interchangeable |