PRIMO.ai

Overview

• How do I leverage AI?
• Courses
• Reading Material

Background

• History of AI
• Current State

AI Breakthroughs

• Case Studies
• Capabilities

AI Fun

• Google AI Experiments
• TensorFlow Playground

How to...

• Strategy & Tactics
• Checklists

Forward Thinking

• Moonshots
• Journey to Singularity
• Creatives

Models

• About 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

• (Deep) Convolutional Neural Network (DCNN/CNN)
• (Deep) Residual Network (DRN) - ResNet

Deonvolutional

• Deconvolutional Neural Network (DN) / Inverse Graphics Network (IGN)

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

• Autoencoder (AE) / Encoder-Decoder
• (Stacked) Denoising Autoencoder (DAE)
• Sparse Autoencoder (SAE)

Unsupervised: Probabilistic/Generative

• Restricted Boltzmann Machine (RBM)
• Deep Belief Network (DBN)
• Variational Autoencoder (VAE)

Competitive

• Generative Adversarial Network (GAN)
• Kohonen Network (KN)/Self Organizing Maps (SOM)

Reinforcement

• Deep Reinforcement Learning
• Deep Q Learning (DQN)

Hierarchical

• Hierarchical Temporal Memory (HTM)

Frameworks

• Frameworks Overview
• Frameworks and libraries in addition to TensorFlow

TensorFlow

• TensorFlow Overview & Tutorials
• TensorFlow.js
• TensorBoard
• TensorFlow Playground
• TensorFlow Serving
• Related...
  • Keras
  • TFLearn
  • Swift

Techniques

Mathematical Background

• Math for Intelligence

Datasets & Information Analysis

• Datasets
• Data Preprocessing & Feature Exploration

Algorithms

• Backpropagation
• Repositories & Other Algorithms

Bag of Tricks

• Activation Functions
• Optimizers
  • Backpropagation
  • Gradient Descent Optimization & Challenges
  • Parameter Initialization
  • Choosing the Right Metric for Evaluating Machine Learning Models
  • Approach to Bias and Variances
• Pooling
• Hyperparameters
• Visualization
• Transfer Learning
• Competitions

Coding

• Javascript
• Python

Platforms: Machine Learning as a Service (MLaaS)

• Service Capabilities
• Other Platforms

Kaggle

• Kaggle Overview
• Kaggle Kernels
  • Jupyter Notebooks
• Kaggle Competitions
  • Passenger Screening

Amazon AWS

• AWS with TensorFlow
• AmazonML
• Deep Learning Amazon Machine Image (DLAMI)
• DeepLens - deep learning enabled video camera

Microsoft Azure

• Azure Process
• Azure with TensorFlow
• ML Studio
• Cognitive Services

Google Cloud AI

• Google Cloud AI With TensorFlow
• ML Engine
• Prediction API
• Google Developers Codelabs
• Google AI Experiments

Research & Development

• Self Learning Artificial Intelligence - AutoML
• Explainable Artificial Intelligence
• Differentiable Neural Computer (DNC)
• Capsule Networks (CapNets)
• Generative Agents
• Messaging & Routing
• Deep Distributed Q Network Partial Observability
• Genetic Algorithms
• Natural Language Inference (NLI) and Recognizing Textual Entailment (RTE)
• 3D Simulation Environments
• Connecting Brains
• Processing Units - CPU, GPU, TPU, VPU
• Other Challenges

Other

• Business-Centric Methodology
• Getting Started - MediaWiki