AdamClarkStandke
Software, Hardware, AI Developer/Patent Attorney/Lawyer/Patent Examiner located and working in the USA.
USPTOUSA
Pinned Repositories
Deep-Reinforcement-Learning-Hands-On-Second-Edition
Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt
Emerging-Neural-Network-Models
Will be implementing and detailing emerging Neural network models such as GNN, Meta-Learning and Memory Augmented models that are still being actively researched and developed to overcome the traditional limitations of Deep learning
GAN_Models
Implementing Different Types of Deep Convolutional Generative Adversarial Networks using different datasets
GenerativeDeepLearning
Repository for documenting different generative learning approaches for creating and implementing synthetic data for machine learning
LangChainTextInteraction
Using Langchain, llms, and promts to interact with scientific text documents for better searching
MachineLearningI
Implementation of the Candidate Elimination Algorithm to do concept learning
MachineLearningII
Artificial Neural Network created with TensorFlow
ReinforcementLearning
Implementing Different Types of Reinforcement-Learning-Algorithms using different environments
Stacked-Ensemble-CBOW-Model
Implementation of a Stacked Ensemble Continuous Bag of Word Model, in which the Meta-Learner is made up of three different submodels: 1) one-dimensional CNN 2) Stacked Bidirectional-Gru with Attention and 3)Stacked Bidirectional-Lstm with Attention
TinyMachineLearning
Developing Embedded/ML Applications for Arduino Nano 33 BLE Sense Rev2 and Raspberry Pi Pico w
AdamClarkStandke's Repositories
AdamClarkStandke/ReinforcementLearning
Implementing Different Types of Reinforcement-Learning-Algorithms using different environments
AdamClarkStandke/GAN_Models
Implementing Different Types of Deep Convolutional Generative Adversarial Networks using different datasets
AdamClarkStandke/Stacked-Ensemble-CBOW-Model
Implementation of a Stacked Ensemble Continuous Bag of Word Model, in which the Meta-Learner is made up of three different submodels: 1) one-dimensional CNN 2) Stacked Bidirectional-Gru with Attention and 3)Stacked Bidirectional-Lstm with Attention
AdamClarkStandke/TinyMachineLearning
Developing Embedded/ML Applications for Arduino Nano 33 BLE Sense Rev2 and Raspberry Pi Pico w
AdamClarkStandke/Deep-Reinforcement-Learning-Hands-On-Second-Edition
Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt
AdamClarkStandke/Emerging-Neural-Network-Models
Will be implementing and detailing emerging Neural network models such as GNN, Meta-Learning and Memory Augmented models that are still being actively researched and developed to overcome the traditional limitations of Deep learning
AdamClarkStandke/GenerativeDeepLearning
Repository for documenting different generative learning approaches for creating and implementing synthetic data for machine learning
AdamClarkStandke/LangChainTextInteraction
Using Langchain, llms, and promts to interact with scientific text documents for better searching
AdamClarkStandke/MachineLearningI
Implementation of the Candidate Elimination Algorithm to do concept learning
AdamClarkStandke/MachineLearningII
Artificial Neural Network created with TensorFlow
AdamClarkStandke/micropython-mpu9250
MicroPython I2C driver for MPU9250 9-axis motion tracking device
AdamClarkStandke/MultinomialNaiveBayes-vs-LogisticRegression
Comparing an Additive Smoothing Multinomial Naive Bayes classifier versus Logistic Regression for Detecting Fake News
AdamClarkStandke/NPL2SQL
Using an LLM to structure table queries
AdamClarkStandke/SeniorResearch
Senior Research Project for CS 498/499. See README.Md for more details.
AdamClarkStandke/TransDiffTemp
Notebooks of me exploring different Transformer and/or Diffusion Models
AdamClarkStandke/Transfer-Learining
Image Classification using transfer learning
AdamClarkStandke/YOLOv5
Using YOLOv5s Object Detection Model on a Raccoon Dataset