Neural Networks and Deep Learning (Artificial Intelligence and Machine Learning): quizzes, mind maps and notes

Top Neural Networks and Deep Learning resources

37 nodes
Deep Feed forward Neural Networks Also known as feedfor... · PERCEPTRON · Some features · Form the basis of man... · Disadvantages Rodrigo Burciaga
84 questions
AI Quiz What is the analogy in Artificial Neural Networks to synaptic efficiencies in biological neurons? Tove .
35 questions
Ai Khara omtenta Below is a truth table for a simple classification problem. Four labelled objects are required to be classi... Pawan Shasawar
116 nodes
3D-DNN 3D Deep Learning Tasks · 3D Model Datasets to ... · Applications of 3D Data · 3D DNN-Training Algor... Dihan Fernando
14 questions
Module 13 Review Nick Feldman
93 nodes
Deep Learning Essentials 7 - Convolutional Net... · 6 - Model Assessment · 5 - Model Training · 4 - Weight Adaptation · 3 - Multilayer Percep... · 2 - Linear Models Mark Otten
11 nodes
RNN Encoder-Decoder Encode a variable-len... · Decode a given fixed-... · From a probabilistic ... · Machine Translation Ahmed Chaouachi
12 cards
Neural Computation Brenna Cantwell

Quizzes

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Notes

Slides

12 slides
NN Sayooj Balakrishnan

About Neural Networks and Deep Learning

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Start with the foundations

Begin with Perceptrons and Sigmoid, a note introducing two types of artificial neuron and stochastic gradient descent. Then open Deep Feed forward Neural Networks, a mind map that introduces multilayer perceptrons. Use the note to focus on the neuron types and the map to see how the feedforward network is described.

For a broader view, Deep Learning Essentials brings together linear models, multilayer perceptrons, weight adaptation, model training and model assessment. You can return to it as you work through the other resources.

Explore learning and network types

The mind map on backpropagation and competitive learning includes gradient descent, computational models and unsupervised networks. Compare its terms with those in the Neural Network mind map, which lists supervised, unsupervised and reinforcement learning alongside feedforward and feedback networks.

Convolutional Neural Networks focuses on filters, or kernels, used to extract features from input information. It also addresses reducing the number of network parameters. These maps offer different starting points depending on the ideas you want to study.

Combine quizzes, maps and flashcards

After looking at a map, try the Artificial Neural Networks quiz. Use the questions to guide another look at the relevant terms in the maps and notes. Neural Computation provides flashcard prompts about artificial neural networks, giving you another way to practice recalling ideas.

The quiz titles include AI Quiz and Module 13 Review. You can open them to see which questions are useful for your study, alongside the small set of other quizzes on the page.

Use the topic in the unit

Neural Networks and Deep Learning is a section of Artificial Intelligence and Machine Learning in Computing and ICT (programming, computer science, digital skills, educational technology). The resources here offer several routes through this section, from neuron types to model training. Choose a map and a quiz to begin your study.

Frequently asked questions

Which resource should I start with?

Perceptrons and Sigmoid is a starting point for studying artificial neuron types and stochastic gradient descent. Follow it with the Deep Feed forward Neural Networks mind map to look at multilayer perceptrons. For a broader overview, Deep Learning Essentials lists topics including linear models, model training and convolutional networks.

What do the mind maps cover?

The page has over 20 mind maps. Their listed topics include feedforward networks, backpropagation, competitive learning and convolutional networks. Deep Learning Essentials also covers model training and assessment. The Neural Network mind map lists learning approaches and applications, so it offers another way to explore the terms on this page.

Are these resources free to use?

Yes. Every resource listed on the page is free to open, study and take without an account. A free account can also save your quiz scores and lets you make your own quizzes, mind maps, flashcards and notes. The listed resources were made by GoConqr users, rather than by GoConqr.

Neural Networks and Deep Learning