課程介紹

Welcome to the best online course for learning about Deep Learning with Python and PyTorch!

PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is rapidly becoming one

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哪些人適合這堂課？

• Intermediate to Advanced Python Developers wanting to learn about Deep Learning with PyTorch

學習目標

• Learn how to use NumPy to format data into arrays
• Use pandas for data manipulation and cleaning
• Learn classic machine learning theory principals
• Use PyTorch Deep Learning Library for image classification
• Use PyTorch with Recurrent Neural Networks for Sequence Time Series Data
• Create state of the art Deep Learning models to work with tabular data

課程介紹

PyTorch has rapidly become one of the most transformative frameworks in the field of Deep Learning. Since its release, PyTorch has completely changed the landscape in the field of deep learning due to its flexibility, and how easy it is to use when b

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哪些人適合這堂課？

• Anyone with an interest in Deep Learning and Computer Vision
• Anyone (no matter the skill level) who wants to transition into the field of Artificial Intelligence
• Entrepreneurs with an interest in working on some of the most cutting edge technologies
• All skill levels are welcome!

學習目標

• Implement Machine and Deep Learning applications with PyTorch
• Build Neural Networks from scratch
• Build complex models through the applied theme of Advanced Imagery and Computer Vision
• Solve complex problems in Computer Vision by harnessing highly sophisticated pre-trained models
• Use style transfer to build sophisticated AI applications

課程介紹

Growing Importance of Deep Learning

Deep learning underpins a lot of important and increasingly important applications today ranging from facial recognition, to self-driving cars, to medical diagnostics and more.  

Made for Anyone  

Although

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哪些人適合這堂課？

• Anyone who wants to learn deep learning
• Deep learning researchers using other frameworks like TensorFlow, Keras, Torch, and Caffe
• Any python programmer

學習目標

• Effectively wield PyTorch, a Python-first framework, to build your deep learning projects
• Master deep learning concepts and implement them in PyTorch

課程介紹

Welcome to PyTorch: Deep Learning and Artificial Intelligence!

Although Google’s Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers arou

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哪些人適合這堂課？

• Beginners to advanced students who want to learn about deep learning and AI in PyTorch

學習目標

• Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
• Predict Stock Returns
• Time Series Forecasting
• Computer Vision
• How to build a Deep Reinforcement Learning Stock Trading Bot
• GANs (Generative Adversarial Networks)
• Recommender Systems
• Image Recognition
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Natural Language Processing (NLP) with Deep Learning
• Demonstrate Moore’s Law using Code
• Transfer Learning to create state-of-the-art image classifiers

課程介紹

UPDATE:

All the code and installation instructions have been updated and verified to work with Pytorch 1.6 !!

Artificial Intelligence is dynamically edging its way into our lives. It is already broadly available and we use it – sometimes even no

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哪些人適合這堂課？

• Anyone interested in artificial intelligence, data science, machine learning, deep learning and reinforcement learning.

學習目標

• Reinforcement Learning basics
• Tabular methods
• Bellman equation
• Q Learning
• Deep Reinforcement Learning
• Learning from video input

課程介紹

Master the Latest and Hottest of Deep Learning Frameworks (PyTorch)  for Python Data Science

THIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH PYTORCH IN PYTHON!

It is a full 5-Hour+ PyTorch Boot Camp that will help you learn basic m

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哪些人適合這堂課？

• Students interested in using the Anaconda environment for Python data science applications
• Students interested in getting started with the PyTorch environment
• Students Interested in Implementing Machine Learning Algorithms using PyTorch
• Students Interested in Implementing Machine Learning Algorithms on Real Life Image Data
• Students Interested in Learning the Basic Theoretical Concepts behind Neural Networks techniques Such as Convolutional neural network
• Implement ANN on Real Data
• Implement Deep Neural Networks
• Implement Convolutional Neural Networks (CNN) on Imagery data
• Build Image Classifiers Using Real Imagery Data and Evaluate Their Performance
• Introduction to Transfer Learning

學習目標

• Deep Learning Basics – Getting started with Anaconda, an important Python data science environment
• Neural Network Python Applications – Configuring the Anaconda environment for getting started with PyTorch
• Introduction to Deep Learning Neural Networks – Theoretical underpinnings of the important concepts (such as deep learning) without the jargon
• AI Neural Networks – Implementing artificial neural networks (ANN) with PyTorch
• Neural Network Model – Implementing deep learning (DL) models with PyTorch
• Deep Learning AI – Implement common machine learning algorithms for Image Classification
• Deep Learning Neural Networks – Implement PyTorch based deep learning algorithms on imagery data

課程介紹

This video course will get you up-and-running with one of the most cutting-edge deep learning libraries: PyTorch. Written in Python, PyTorch is grabbing the attention of all data science professionals due to its ease of use over other libraries and i

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哪些人適合這堂課？

• This course is for Python programmers who have some knowledge of machine learning and want to build Deep Learning systems with PyTorch.

學習目標

• Understand PyTorch and Deep Learning concepts
• Build your neural network using Deep Learning techniques in PyTorch.
• Perform basic operations on your dataset using tensors and variables
• Build artificial neural networks in Python with GPU acceleration
• See how CNN works in PyTorch with a simple computer vision example
• Train your RNN model from scratch for text generation
• Use Auto Encoders in PyTorch to remove noise from images
• Perform reinforcement learning to solve OpenAI’s Cartpole task
• Extend your knowledge of Deep Learning by using PyTorch to solve your own machine learning problems

課程介紹

深度学习框架-PyTorch实战课程旨在帮助同学们快速掌握PyTorch框架核心模块使用方法与项目应用实例，让同学们熟练使用PyTorch框架进行项目开发。课程内容全部以实战为导向，基于当下计算机视觉与自然语言处理中经典项目进行实例讲解，通过Debug模式详解项目中每一行代码的作用与效果，整体风格通俗易懂。

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哪些人適合這堂課？

• 人工智能方向的同学们
• 深度学习方向的同学们

學習目標

• 掌握深度学习必备经典算法
• 掌握深度学习框架PyTorch核心模块使用方法
• 熟练使用PyTorch框架进行实际开发
• 熟练应用PyTorch框架构建图像识别项目
• 熟练应用PyTorch框架构建自然语言处理项目
• 掌握文字识别OCR原理及其项目构建方法
• 掌握视频分析与3D卷积原理及实战方法
• 掌握文本分类方法及其网络架构
• 熟练应用PyTorch模板进行实际项目工作
• 掌握GAN网络架构原理
• 熟练使用cycleGan进行图像合成

課程介紹

The course starts by introducing you to the main concepts in Neural Networks (NN) and how do they work. Then we will implement a NN from scratch using Pytorch. After that, a quick introduction to Federated Learning architecture. Then, we will start b

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哪些人適合這堂課？

• Federated Learning enthusiasts

學習目標

• Introduction to Deep Learning and Neural Networks
• Introduction to Federated Learning
• Build Neural Networks from scratch using PyTorch
• Load your datasets in IID, non-IID, and non-IID unbalanced settings
• Introduction to PySyft
• Federated Learning techniques (FedAvg, FedSGD, FedProx, FedDANE)
• Build your custom optimizer using PyTorch
• Introduction to Differential Privacy
• Implement FedAvg using Differential Privacy
• Federated Learning on cloud
• Implement FedAvg on cloud

課程介紹

基于深度学习的语音识别实战课程主要包括三部分内容：1.经典论文算法讲解；2.算法源码解读；3.项目实战；通俗讲解语音识别领域当下经典论文思想，详细解读源码中每一核心模块并基于真实数据集展开项目实战。整体课程覆盖语音识别领域四大核心主题：语音识别，语音分离，语音转换，语音合成；每一主题均按照论文思想解读，源码分析，项目实战顺序进行讲解。提供课程所需全部数据集，代码，PPT课件。

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哪些人適合這堂課？

• 人工智能，深度学习方向的同学们

學習目標

• 掌握语音经典算法及其应用领域
• 熟练使用PyTorch框架构建语音识别模型
• 掌握语音识别领域经典论文算法
• 熟悉语音数据预处理方法
• 熟练使用深度学习框架进行语音识别任务开发
• 熟悉语音分离技术落地方案
• 熟练使用PyTorch框架构建语音分离模型
• 掌握语音合成最新论文及其算法思想
• 熟练使用PyTorch构建语音合成模型
• 掌握变声器构建原理及其应用
• 熟练使用PyTorch框架构建变声器模型