Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Machine Learning Toolkit for Kubernetes
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
A curated list of applied machine learning and data science notebooks and libraries across different industries.
Prophecis is a one-stop cloud native machine learning platform.
CNN image classifier implemented in Keras Notebook 🖼️.
This project provides code examples for SAP HANA Predictive and Machine Learning scenarios and is educational content. It covers simple Predictive Analysis Library SQL examples as well as complete SAP HANA design-time “ML scenario”-application content or HANA-ML Python Notebook examples.
Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content
A collection of notebooks of my Machine Learning class written in python 3
Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
Helmut Hoffer von Ankershoffen experimenting with arm64 based NVIDIA Jetson (Nano and AGX Xavier) edge devices running Kubernetes (K8s) for machine learning (ML) including Jupyter Notebooks, TensorFlow Training and TensorFlow Serving using CUDA for smart IoT.
Stress classifier with AutoML
Collaboration platform for data science projects & Jupyter notebooks
A repository for sharing ipynb's of my experiments with ML. Some notebooks are 'old' by now and might no longer work 'out of the box'.
A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.
Implementation of several ML models on real-world datasets with detailed explanation in notebooks.
This repository contains the Python code for implementing facial recognition in Jupyter Notebook using both Machine Learning classification algorithms and neural networks. It also contains a CSV of facial data for classifying faces using the Python code. Feel free to copy the files and start recognizing faces!
📚 Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.