Advanced Computer Vision with TensorFlow
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Advanced Deployment Scenarios with TensorFlow
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Advanced Learning Algorithms
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Advanced Retrieval for AI with Chroma
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AI Agentic Design Patterns with AutoGen
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AI Agents in LangGraph
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AI and Climate Change
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AI and Disaster Management
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AI and Public Health
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AI For Everyone
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AI for Medical Diagnosis
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AI for Medical Prognosis
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AI For Medical Treatment
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AI Python for Beginners
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AI-Powered Software and System Design
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Apply Generative Adversarial Networks (GANs)
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Browser-based Models with TensorFlow.js
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Build Basic Generative Adversarial Networks (GANs)
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Build Better Generative Adversarial Networks (GANs)
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Build LLM Apps with LangChain.js
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Building Agentic RAG with LlamaIndex
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Building AI Applications with Haystack
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Building Applications with Vector Databases
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Building Multimodal Search and RAG
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Building Systems with the ChatGPT API
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Building Your Own Database Agent
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Calculus for Machine Learning and Data Science
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Carbon Aware Computing for GenAI Developers
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ChatGPT Prompt Engineering for Developers
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Convolutional Neural Networks
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Convolutional Neural Networks in TensorFlow
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Custom and Distributed Training with TensorFlow
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Custom Models, Layers, and Loss Functions with TensorFlow
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Data Modeling, Transformation, and Serving
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Data Pipelines with TensorFlow Data Services
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Data Storage and Queries
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Device-based Models with TensorFlow Lite
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Efficiently Serving LLMs
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Embedding Models: From Architecture to Implementation
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Evaluating and Debugging Generative AI
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Finetuning Large Language Models
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Function-Calling and Data Extraction with LLMs
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Functions, Tools and Agents with LangChain
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Generative AI for Everyone
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Generative AI with Large Language Models
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Generative Deep Learning with TensorFlow
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Getting Started with Mistral
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How Diffusion Models Work
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Improving Accuracy of LLM Applications
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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
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Introducing Multimodal Llama 3.2
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Introduction to Data Engineering
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Introduction to Generative AI for Software Development
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Introduction to On-Device AI
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Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
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JavaScript RAG Web Apps with LlamaIndex
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Knowledge Graphs for RAG
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LangChain Chat with Your Data
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LangChain for LLM Application Development
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Large Language Models with Semantic Search
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Linear Algebra for Machine Learning and Data Science
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LLMOps
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Machine Learning in Production
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Multi AI Agent Systems with crewAI
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Natural Language Processing in TensorFlow
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Natural Language Processing with Attention Models
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Natural Language Processing with Classification and Vector Spaces
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Natural Language Processing with Probabilistic Models
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Natural Language Processing with Sequence Models
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Neural Networks and Deep Learning
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Open Source Models with Hugging Face
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Pair Programming with a Large Language Model
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Preprocessing Unstructured Data for LLM Applications
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Pretraining LLMs
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Probability & Statistics for Machine Learning & Data Science
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Prompt Compression and Query Optimization
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Prompt Engineering with Llama 2&3
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Quality and Safety for LLM Applications
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Quantization Fundamentals with Hugging Face
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Quantization in Depth
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Red Teaming LLM Applications
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Reinforcement Learning from Human Feedback
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Retrieval Optimization: Tokenization to Vector Quantization
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Sequence Models
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Sequences, Time Series and Prediction
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Source Systems, Data Ingestion, and Pipelines
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Structuring Machine Learning Projects
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Supervised Machine Learning: Regression and Classification
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Team Software Engineering with AI
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Understanding and Applying Text Embeddings
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Unsupervised Learning, Recommenders, Reinforcement Learning
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Vector Databases: from Embeddings to Applications
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AI For Everyone （すべての人のためのAIリテラシー講座）
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AI、機械学習、ディープラーニングのための TensorFlow 入門
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Améliorez les réseaux neuronaux profonds
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IA para todos
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IA para todos
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KI für alle
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L’IA pour tous
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Modèles de séquence
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Neuronale Netze und Deep Learning
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Réseaux neuronaux convolutifs
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Réseaux neuronaux et Deep Learning
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Structurer des projets d’apprentissage automatique
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TensorFlow を使った畳み込みニューラルネットワーク
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Искусственный Интеллект (ИИ) для всех
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Нейронные сети и глубокое обучение
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Повышение эффективности глубоких нейросетей
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Последовательные модели
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Сверточные нейронные сети
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Структурирование проектов по машинному обучению
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الذكاء الاصطناعي للجميع
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الشبكات العصبونية الالتفافية
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الشبكات العصبية والتعلم العميق
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النماذج المتعاقبة
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تعزيز الشبكات العصبية : ضبط وتحسين مقياس فرط المعلمات
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هيكلة مشاريع التعلم الآلي
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머신 러닝 프로젝트 구조화
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시퀀스 모델
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신경망 및 딥 러닝
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심층 신경망 개선: 하이퍼파라미터 튜닝, 정규화 및 최적화
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컨볼루션 신경망
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