AdArya125 / Primer-to-Machine-LearningLinks
'Primer to Machine Learning' is a comprehensive guide covering essential topics in machine learning, including statistics, data preprocessing, supervised and unsupervised learning, neural networks, deep learning, NLP, time series analysis, and reinforcement learning. Perfect for beginners and intermediates.
☆21Updated last year
Alternatives and similar repositories for Primer-to-Machine-Learning
Users that are interested in Primer-to-Machine-Learning are comparing it to the libraries listed below
Sorting:
- Welcome to 6.86x Machine Learning with Python–From Linear Models to Deep Learning. Machine learning methods are commonly used across eng…☆13Updated 5 years ago
- Implementation of Dynamic Computation Offloading Control Logic in a Software-Defined Vehicle (SDV) System☆11Updated last year
- Data Traceability and Safety in the Cloud and Edge☆12Updated 3 years ago
- ROS 기반 자율주행 application의 로드밸런싱을 위한 computation offloading 기술 개발☆19Updated last year
- ☆10Updated 10 months ago
- Stock market data can be interesting to analyze and as a further incentive, strong predictive models can have large financial payoff. The…☆24Updated 7 years ago
- ROS2 기반 자율주행 application의 로드밸런싱을 위한 computation offloading 기술 개발☆16Updated last year
- [ICML 2024 Oral] Consistent Adversarial Robust Deep Q Networks (CAR-DQN)☆15Updated 10 months ago
- ☆17Updated last year
- My implementation of a deep q learning network learning to play pong.☆10Updated 4 years ago
- I predict air quality index of a city in China using a Long Short Term Memory (LSTM) neural network. for a year. Executed time series ana…☆29Updated 5 years ago
- ☆21Updated 2 years ago
- a Federated Learning Framework adapted for resource-constrained environments, focusing on IoT devices☆10Updated 2 months ago
- Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras base on tutorial of Jason Brownlee☆21Updated 7 years ago
- My solutions for https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning☆33Updated 3 years ago
- Working examples of Deep Q Network of Reinforcement Learning☆13Updated 5 years ago
- Code for paper Stock trading rule discovery with double deep Q-network☆14Updated 2 years ago
- Automated stock trading strategy using deep reinforcement learning and recurrent neural networks☆13Updated last year
- https://youtu.be/Q82a93hjxJE☆47Updated 2 weeks ago
- Predicting for Customers, whether they will buy car insurance or not.☆10Updated 4 years ago
- Fully coded with Google Colab.☆27Updated 4 years ago
- Teaching the Donkey car to drive a track in the simulator using State Representation Learning and different Reinforcement Learning Algori…☆10Updated 4 years ago
- Adaptation of DQN, DDQN and COMA for multi-agent Gym environments☆12Updated 2 years ago
- 💳 Creates a new gym environment for credit-card anomaly detection using Deep Q-Networks (DQN) and leverages Open AI's Gym toolkit to all…☆18Updated 5 years ago
- Google Stock Price Prediction Using RNN - LSTM☆15Updated 6 years ago
- Solution to Cartpole balancing problem with the help of reinforcement learning and Deep Neural Networks.☆11Updated 2 years ago
- Official implementation of the UMDQN algorithm presented in the scientific research paper entitled "Distributional Reinforcement Learning…☆11Updated 3 years ago
- Coursera-Fundamentals of Reinforcement Learning Specialization.☆15Updated last year
- Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effecti…☆12Updated 6 years ago
- Implementation of Deep Q-network to play the game 2048 using Keras.☆13Updated 4 years ago