PacktPublishing / A-Handbook-of-Mathematical-Models-with-Python
A Handbook of Mathematical Models with Python, published by Packt
☆22Updated 2 months ago
Alternatives and similar repositories for A-Handbook-of-Mathematical-Models-with-Python:
Users that are interested in A-Handbook-of-Mathematical-Models-with-Python are comparing it to the libraries listed below
- Time Series Analysis with Python Cookbook, Second Edition - Published by Packt☆37Updated last week
- Python Feature Engineering Cookbook, Third Edition, published by Packt☆51Updated 7 months ago
- Data Cleaning and Exploration with Machine Learning☆53Updated 2 years ago
- Interpretable ML with Python, 2E - published by Packt☆94Updated last year
- Code repository for "Modern Statistics: A Computer Based Approach with Python" and "Industrial Statistics: A Computer Based Approach with…☆101Updated 8 months ago
- Machine Learning Using TensorFlow Cookbook, published by Packt☆68Updated 2 years ago
- Building Statistical Models in Python, Published by Packt☆28Updated 2 months ago
- Comet for Data Science, published by Packt☆42Updated last year
- Code repository for the book feature selection in machine learning☆28Updated last week
- Hands-On Web Scraping with Python - Second Edition, published by Packt☆50Updated last year
- Code Repository for The Kaggle Workbook, Published by Packt☆118Updated last year
- Machine Learning for Streaming Data with Python, published by Packt☆69Updated last year
- The Regularization Cookbook, published by Packt☆12Updated 2 months ago
- Data Augmentation with Python, published by Packt☆36Updated 5 months ago
- ☆125Updated 2 months ago
- Forecasting Time Series Data with Prophet- Second Edition, published by Packt☆32Updated last year
- Machine Learning Engineering on AWS, published by Packt☆67Updated last year
- Hands-On Simulation Modeling with Python, Second Edition, published by Packt☆32Updated last year
- A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)☆85Updated last year
- Here are the notebooks for the Gaussian Processes and Bayesian Optimization course. The notebooks can be executed in Google Colab.☆27Updated 9 months ago
- Machine Learning Model Serving Patterns and Best Practices☆35Updated last year
- ☆33Updated last year
- Machine Learning Techniques for Text, Published by Packt☆34Updated last year
- Code Repository for Data Analysis with Pandas and Python(v), Published by Packt☆50Updated last week
- ☆40Updated last year
- B21145 - Deep Learning for Time Series Data Cookbook☆54Updated 10 months ago
- Data Science, Analytics & AI for Business & the Real World™, published by Packt☆33Updated 2 years ago
- Cleaning Data for Effective Data Science, published by Packt☆97Updated 2 years ago
- A pipeline to detect data drift and retrain the model when there is drift☆23Updated last year
- A Practical Approach to Timeseries Forecasting using Python, published by Packt☆11Updated 7 months ago