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Everything about Deep learning
Branch of machine learning
In machine learning, deep learning (DL) focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and revolves around stacking artificial neurons into layers and "training" them to process data. The adjective "deep" refers to the use of multiple layers in the network. Methods used can be supervised, semi-supervised or unsupervised. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Deep learningA 5-minute orientation
- Skim a recent paper: Transformational leadership for deeper learning: shaping innovative school practices for enhanced learningInfluential work since 2022
- Pick up a classic book: Deeper Learning, Dialogic Learning, and Critical ThinkingThe most-reprinted book on the subject
- Read the landmark paper: Dendritic Computing: Branching Deeper into Machine LearningCited 44 times
- Go sideways: Long short-term memoryA closely related topic
- Go sideways: Recurrent neural networkA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Dendritic Computing: Branching Deeper into Machine Learning
Driving Deeper Learning by Assessment
Teaching for deeper political learning: a design experiment
Social Learning: Peering Deeper into Ape Culture
Computer-Based Learning Environments for Deeper Learning in Problem-Solving Contexts
Does Student Involvement in Practical Learning Strengthen Deeper Learning Competencies?
Deeper and cheaper machine learning [Top Tech 2017]
Deeper learning in electrocatalysis: realizing opportunities and addressing challenges
🆕 Influential since 2022
Transformational leadership for deeper learning: shaping innovative school practices for enhanced learning
Learning the User’s Deeper Preferences for Multi-modal Recommendation Systems
Deciphering plant transcriptomes: Leveraging machine learning for deeper insights
Multilayer vectorization to develop a deeper image feature learning model
Fostering autonomous motivation: a deeper evaluation of gamified learning
📚 Books worth reading
- 📕Deeper Learning, Dialogic Learning, and Critical ThinkingEmmanuel Manalo · 2019
- 📕Stepping up Lesson StudyAki Murata, Christine Kim-Eng Lee · 2020
Deeper LearningHang Hu · 2022
Leadership for Deeper LearningJayson W. Richardson, Justin Bathon · 2021
Deeper Learning in LeadershipDennis C. Roberts · 2007
Beyond CLILDo Coyle, Oliver Meyer · 2021
Deeper Learning Companion for CLILDo Coyle, Oliver Meyer · 2023
Python machine learningSebastian Raschka · 2015
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Long short-term memory Long short-term memory (LSTM) is a type of recurrent neural network (RNN) aimed at mitigating the vanishing gradient problem commonly encountered by traditional…
- Recurrent neural network In artificial neural networks, recurrent neural networks (RNNs) are designed for processing sequential data, such as text, speech, and time series, where…
- Types of artificial neural networks Types of neural networks (NN) include a family of techniques. The simplest types have static components, including number of units, number of layers, unit…
- History of artificial neural networks Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. While the computational implementations of ANNs…
- Jürgen Schmidhuber Jürgen Schmidhuber (born 17 January 1963) is a German computer scientist in the field of artificial intelligence, specifically artificial neural networks…
- Neural network (machine learning) In machine learning, a neural network (NN) or artificial neural network (ANN) is a computational model inspired by the structure and functions of biological…
- Echo state network An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer (with typically…
- Convolutional neural network A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep…