Difference between revisions of "PRIMO.ai"
(→Research & Development) |
(→Platforms: Machine Learning as a Service (MLaaS)) |
||
| Line 116: | Line 116: | ||
== Platforms: Machine Learning as a Service (MLaaS) == | == Platforms: Machine Learning as a Service (MLaaS) == | ||
| − | |||
* [[Service Capabilities]] | * [[Service Capabilities]] | ||
* [[Other Platforms]] | * [[Other Platforms]] | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
==== Amazon AWS ==== | ==== Amazon AWS ==== | ||
| − | |||
* [[AWS with TensorFlow]] | * [[AWS with TensorFlow]] | ||
* [[AmazonML]] | * [[AmazonML]] | ||
* [[Deep Learning Amazon Machine Image (DLAMI)]] | * [[Deep Learning Amazon Machine Image (DLAMI)]] | ||
* [[DeepLens - deep learning enabled video camera]] | * [[DeepLens - deep learning enabled video camera]] | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
==== Google Cloud AI ==== | ==== Google Cloud AI ==== | ||
| − | |||
* [[Google Cloud AI With TensorFlow]] | * [[Google Cloud AI With TensorFlow]] | ||
* [[ML Engine]] | * [[ML Engine]] | ||
| Line 148: | Line 132: | ||
* [http://experiments.withgoogle.com/collection/ai Google AI Experiments] | * [http://experiments.withgoogle.com/collection/ai Google AI Experiments] | ||
* [http://cloud.google.com/vision/ Cloud Vision API - drag & drop picture on webpage] | * [http://cloud.google.com/vision/ Cloud Vision API - drag & drop picture on webpage] | ||
| + | |||
| + | ==== Kaggle ==== | ||
| + | * [[Kaggle Overview]] | ||
| + | * [[Kaggle Kernels]] | ||
| + | ** [[Jupyter Notebooks]] | ||
| + | * [[Kaggle Competitions]] | ||
| + | ** [[Passenger Screening]] | ||
| + | |||
| + | ==== Microsoft Azure ==== | ||
| + | * [[Azure Process]] | ||
| + | * [[Azure with TensorFlow]] | ||
| + | * [[ML Studio]] | ||
| + | * [[Cognitive Services]] | ||
== Research & Development == | == Research & Development == | ||
Revision as of 15:09, 26 May 2018
Contents
Overview
Background
AI Breakthroughs
AI Fun
How to...
Forward Thinking
Models
Supervised
- Support Vector Machine (SVM)
- Hopfield Network (HN)
- Energy-based Model (EBN)
- Naive Bayes
- Markov Model (Chain, Discrete Time, Continuous Tme, Hidden)
- Perceptron (P)
- Feed Forward Neural Network (FF or FFNN)
- Artificial Neural Network (ANN)
- Deep Neural Network (DNN)
Convolutional
Deonvolutional
Sequence
- Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)
- Attention Model
- Sequence to Sequence (Seq2Seq)
- (Tree) Recursive Neural (Tensor) Network (RNTN)
- Neural Turing Machine
Unsupervised: Non-Probabilistic
Unsupervised: Probabilistic/Generative
Competitive
Reinforcement
Hierarchical
Frameworks
TensorFlow
- TensorFlow Overview & Tutorials
- TensorFlow.js
- TensorBoard
- TensorFlow Playground
- TensorFlow Serving
- Related...
Techniques
Mathematical Background
Datasets & Information Analysis
Algorithms
Bag of Tricks
- Activation Functions
- Optimizers
- Pooling
- Hyperparameters
- Visualization
- Transfer Learning
- Competitions
Coding
Platforms: Machine Learning as a Service (MLaaS)
Amazon AWS
- AWS with TensorFlow
- AmazonML
- Deep Learning Amazon Machine Image (DLAMI)
- DeepLens - deep learning enabled video camera
Google Cloud AI
- Google Cloud AI With TensorFlow
- ML Engine
- Prediction API
- Google Developers Codelabs
- Google AI Experiments
- Cloud Vision API - drag & drop picture on webpage
Kaggle
Microsoft Azure
Research & Development
- Self Learning Artificial Intelligence - AutoML
- Explainable Artificial Intelligence
- Differentiable Neural Computer (DNC)
- Genetic Algorithms
- Natural Language Inference (NLI) and Recognizing Textual Entailment (RTE)
- 3D Simulation Environments
- Connecting Brains
- Architectures
- Other Challenges
