Pearson
Learning Deep Learning 专项课程
Pearson

Learning Deep Learning 专项课程

A Complete Guide to Deep Learning for AI. Learn the essential building blocks of deep neural networks and build advanced architectures.

Pearson

位教师：Pearson

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4 周 完成
在 5 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Build and optimize deep learning models for tasks such as image classification, language modeling, machine translation, and multimodal applications using TensorFlow and PyTorch.

  • Understand and apply advanced architectures, including convolutional neural networks, recurrent neural networks, transformers, and large language models.

  • Develop practical skills in data handling, model evaluation, regularization, and ethical AI deployment for real-world scenarios.

您将获得的技能

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授课语言：英语（English）
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专业化 - 3门课程系列

Learning Deep Learning: Unit 1

Learning Deep Learning: Unit 1

第 1 门课程5小时

您将学到什么

  • Grasp the core concepts and history of deep learning, including neural network fundamentals and training algorithms.

  • Develop hands-on skills in building, training, and evaluating neural networks using TensorFlow and PyTorch.

  • Apply advanced techniques to solve real-world problems in image classification, language processing, and multimodal AI.

  • Understand practical considerations and ethical aspects of deploying deep learning in real-world applications.

您将获得的技能

类别：Tensorflow
类别：PyTorch (Machine Learning Library)
类别：Deep Learning
类别：Artificial Neural Networks
类别：Network Architecture
类别：Python Programming
类别：Data Processing
类别：Algorithms
类别：Large Language Modeling
类别：Machine Learning
类别：Artificial Intelligence and Machine Learning (AI/ML)
Learning Deep Learning: Unit 2

Learning Deep Learning: Unit 2

第 2 门课程7小时

您将学到什么

  • Build and optimize convolutional neural networks for advanced image classification tasks using TensorFlow and PyTorch.

  • Apply recurrent neural networks and LSTMs to sequential data problems, including time series forecasting and text autocompletion.

  • Develop neural language models and implement word embeddings for robust natural language processing.

  • Design and implement encoder-decoder architectures and Transformer models for machine translation and sequence-to-sequence tasks.

您将获得的技能

类别：Deep Learning
类别：Natural Language Processing
类别：Artificial Neural Networks
类别：Computer Vision
类别：Tensorflow
类别：PyTorch (Machine Learning Library)
类别：Time Series Analysis and Forecasting
类别：Forecasting
类别：Machine Learning Methods
类别：Image Analysis
类别：Network Architecture
Learning Deep Learning: Unit 3

Learning Deep Learning: Unit 3

第 3 门课程6小时

您将学到什么

  • Master large language models and transformer architectures for advanced natural language processing applications.

  • Build and deploy multimodal networks that integrate multiple data types, such as text and images.

  • Implement multitask learning and solve advanced computer vision problems, including object detection and segmentation.

  • Apply ethical principles and practical strategies for tuning and deploying deep learning models in real-world settings.

您将获得的技能

类别：Multimodal Prompts
类别：Tensorflow
类别：Large Language Modeling
类别：PyTorch (Machine Learning Library)
类别：Computer Vision
类别：Deep Learning
类别：Machine Learning Methods
类别：Responsible AI
类别：Application Deployment
类别：Natural Language Processing
类别：Network Model
类别：Generative AI
类别：Data Ethics
类别：LLM Application
类别：Prompt Engineering
类别：Image Analysis
类别：Artificial Neural Networks
类别：Artificial Intelligence
类别：Performance Tuning
类别：Applied Machine Learning

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