AI Glossary

Techniques

Dive into the 'Techniques' section and unravel the intricate processes powering AI's magic. From the nuances of data preparation to the prowess of transformers, journey through the stages that bring AI to life.

Artificial intelligence is anchored by a vast array of techniques that define its functionality and capabilities.

Model Development:

Dive into the stages of AI model progression:

Data Handling: Grasp the intricacies of sourcing, cleaning, and preprocessing data—the foundation of any AI system.
Training & Validation: Understand the balance of model learning, the art of avoiding overfitting, and the pursuit of generality.
Deployment & Scaling: Discover how trained models are seamlessly integrated into real-world applications and scaled to handle vast datasets.

Architectural Explorations:

Venture into the blueprint of AI systems:

Classical Models: Revisit the foundational architectures that paved the way, from decision trees to support vector machines.
Neural Networks: Dive deep into the layers of perceptrons, convolutional networks, and recurrent models.
Transformative Designs: Encounter advanced structures like transformers, responsible for breakthroughs such as GPT and BERT.

For both budding AI enthusiasts and seasoned experts, the "Techniques" section serves as a bridge to the underlying processes and methods that make AI the formidable force it is today.

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Metacognitive Learning Models AI and Medicine Grounding Probabilistic Models in Machine Learning Knowledge Distillation Inference Engine Emergent Behavior Double Descent Bayesian Machine Learning Batch Gradient Descent Voice Cloning Homograph Disambiguation Grapheme-to-Phoneme Conversion (G2P)Deep Learning Articulatory Synthesis AI Voice Agents AI Agents Text-to-Speech Models Neural Text-to-Speech (NTTS)Pooling (Machine Learning)Pretraining Machine Learning in Algorithmic Trading Test Data Set Bias-Variance Tradeoff Learning Rate Logits Inductive Bias Continuous Learning Systems Supervised Learning Autoregressive Model Auto Classification Hidden Layer Multitask Prompt Tuning Multi-task Learning Machine Learning Neuron Semi-Supervised Learning Rectified Linear Unit (ReLU)Validation Data Set Incremental Learning Diffusion Clustering Algorithms Few Shot Learning Machine Learning Life Cycle Management Named Entity Recognition AI Robustness Information Retrieval Augmented Intelligence Collaborative Filtering Cognitive Architectures AI Prototyping AI and Big Data AI Scalability AI Literacy Machine Learning Bias Image Recognition AI Resilience Synthetic Data for AI Training Objective Function Data Drift Self-healing AI Spike Neural Networks Human-centered AI Federated Learning Uncertainty in Machine Learning Parametric Neural Networks Limited Memory AI Naive Bayes Classifier AI Transparency Human-in-the-Loop AI Machine Learning Preprocessing AI Privacy Multi-Agent Systems Generative Teaching Networks AI Interpretability AI Regulation Human Augmentation with AI Feature Store for Machine Learning Decision Intelligence Chatbots Quantum Machine Learning Algorithms Computational Phenotyping Counterfactual Explanations in AI Context-Aware Computing Instruction Tuning AI Simulation Ethical AI AI Oversight AI Safety Symbolic AI AI Guardrails Composite AI Gradient Clipping Generative Adversarial Networks (GANs)Rule-Based AI AI Assistants Activation Functions Dall-E Prompt Engineering Hyperparameters AI and Education Chess bots Midjourney (Image Generation)DistilBERT Mistral XLNet Benchmarking Llama 2 Sentiment Analysis LLM Collection ChatGPT Mixture of Experts Latent Dirichlet Allocation (LDA)RoBERTa RLHF Multimodal AI Transformers Winnow Algorithm k-Shingles Flajolet-Martin Algorithm CURE Algorithm Online Gradient Descent Zero-shot Classification Models Curse of Dimensionality Backpropagation Dimensionality Reduction Multimodal Learning Gaussian Processes AI Voice Transfer Gated Recurrent Unit Prompt Chaining Approximate Dynamic Programming Adversarial Machine Learning Deep Reinforcement Learning Speech-to-text models Feedforward Neural Network BERT Gradient Boosting Machines (GBMs)Retrieval-Augmented Generation (RAG)Perceptron Overfitting and Underfitting Machine Learning Large Language Model (LLM)Graphics Processing Unit (GPU)Diffusion Models Classification Tensor Processing Unit (TPU)Natural Language Processing (NLP)Google's Bard OpenAI Whisper Sequence Modeling Precision and Recall Semantic Kernel Fine Tuning in Deep Learning Gradient Scaling AlphaGo Zero Cognitive Map Keyphrase Extraction Multimodal AI Models and Modalities Hidden Markov Models (HMMs)AI Hardware Natural Language Generation (NLG)Natural Language Understanding (NLU)Tokenization Word Embeddings AI and Finance AlphaGo AI Recommendation Algorithms Binary Classification AI AI Generated Music Neuralink AI Video Generation OpenAI Sora Hooke-Jeeves Algorithm Mamba Central Processing Unit (CPU)Generative AI Representation Learning AI in Customer Service Conditional Variational Autoencoders Conversational AI Packages Models Fundamentals Datasets Techniques AI Lifecycle Management AI Monitoring Machine Translation MLOps Monte Carlo Learning Principal Component Analysis Reproducibility in Machine Learning Restricted Boltzmann Machines Support Vector Machines (SVM)Topic Modeling Vanishing and Exploding Gradients Data Labeling F1 Score in Machine Learning Expectation Maximization Beam Search Algorithm Embedding Layer Differential Privacy Data Poisoning Causal Inference Capsule Neural Network Attention Mechanisms Domain Adaptation Evolutionary Algorithms Contrastive Learning Explainable AI Affective AI Semantic Networks Data Augmentation Convolutional Neural Networks Cognitive Computing End-to-end Learning Prompt Tuning Model Drift Neural Radiance Fields Regularization Natural Language Querying (NLQ)Foundation Models Forward Propagation F2 Score AI Ethics Transfer Learning AI Alignment Whisper v3 Whisper v2 Semi-structured data AI Hallucinations Matplotlib NumPy Scikit-learn SciPy Keras TensorFlow Seaborn Python Package PyTorch Natural Language Toolkit (NLTK)Pandas Ego 4D The Pile Common Crawl Datasets SQuAD Intelligent Document Processing Hyperparameter Tuning Markov Decision Process Graph Neural Networks Neural Architecture Search Ablation Model Interpretability Out-of-Distribution Detection Recurrent Neural Networks Active Learning (Machine Learning)Imbalanced Data Loss Function Unsupervised Learning AdaGrad Acoustic Models Concatenative Synthesis Candidate Sampling Computational Creativity AI Emotion Recognition Knowledge Representation and Reasoning AI Speech Enhancement Eco-friendly AI Metaheuristic Algorithms Statistical Relational Learning Deepfake Detection One-Shot Learning Semantic Search Algorithms Artificial Super Intelligence Computational Linguistics Computational Semantics Part-of-Speech Tagging Random Forest Neural Style Transfer Neuroevolution Association Rule Learning Autoencoder Data Scarcity Decision Tree Ensemble Learning Entropy in Machine Learning Corpus in NLP Confirmation Bias in Machine Learning Confidence Intervals in Machine Learning Cross Validation in Machine Learning Accuracy in Machine Learning Clustering in Machine Learning Boosting in Machine Learning Epoch in Machine Learning Feature Learning Feature Selection Genetic Algorithms in AI Ground Truth in Machine Learning Hybrid AI AI Detection AI Standards AI Steering ImageNet Learning To Rank Applications

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