{"id":4124,"date":"2025-08-05T23:04:09","date_gmt":"2025-08-05T23:04:09","guid":{"rendered":"https:\/\/uplatz.com\/blog\/?p=4124"},"modified":"2025-08-06T01:20:18","modified_gmt":"2025-08-06T01:20:18","slug":"ai-ml-dl-flashcards","status":"publish","type":"post","link":"https:\/\/uplatz.com\/blog\/ai-ml-dl-flashcards\/","title":{"rendered":"AI\/ML\/DL Flashcards"},"content":{"rendered":"

<\/p>\n

\n
\n
\n
Supervised Learning<\/div>\n
A type of machine learning where the model learns from labeled training data to make predictions or classify data points.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Underfitting<\/div>\n
Occurs when a model is too simple to capture the underlying patterns in data, resulting in poor performance on both training and test sets.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Overfitting<\/div>\n
When a model learns the training data too well, including noise and outliers, and performs poorly on new, unseen data.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Gradient Descent<\/div>\n
An optimization algorithm used to minimize the loss function by iteratively updating model parameters in the opposite direction of the gradient.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Evaluation Metrics<\/div>\n
Methods to assess model performance such as accuracy, precision, recall, F1-score, and confusion matrix.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Activation Function<\/div>\n
Functions like ReLU, Sigmoid, or Tanh that introduce non-linearity into neural networks, allowing them to learn complex patterns.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
CNN<\/div>\n
Convolutional Neural Networks are specialized deep learning models primarily used for processing grid-like data such as images.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Deep Learning<\/div>\n
A subset of machine learning using neural networks with many layers to model complex patterns in large datasets.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Attention<\/div>\n
A mechanism that enables models to focus on relevant parts of the input, crucial in NLP and transformer architectures.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Transformers<\/div>\n
Deep learning models that rely entirely on attention mechanisms and are foundational to modern NLP (e.g., BERT, GPT).<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Transfer Learning<\/div>\n
A technique where a pre-trained model is reused on a new but related problem, speeding up training and improving performance.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
Reinforcement Learning<\/div>\n
A learning paradigm where agents take actions in an environment to maximize cumulative reward over time.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Supervised Learning A type of machine learning where the model learns from labeled training data to make predictions or classify data points. Underfitting Occurs when a model is too simple Read More …<\/a><\/span><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[170,169,2392,131],"tags":[],"class_list":["post-4124","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-deep-learning","category-flashcards","category-machine-learning"],"yoast_head":"\nAI\/ML\/DL Flashcards | Uplatz Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/uplatz.com\/blog\/ai-ml-dl-flashcards\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI\/ML\/DL Flashcards | Uplatz Blog\" \/>\n<meta property=\"og:description\" content=\"Supervised Learning A type of machine learning where the model learns from labeled training data to make predictions or classify data points. 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