Results for "workflow of machine learning projects"
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Deployment, AI Orchestration, AI Workflows, Generative AI, Google Cloud Platform, Data Modeling, Continuous Monitoring, Data Pipelines, Model Training, Feature Engineering, Model Optimization, DevOps, Agentic Workflows, Generative AI Agents, Data Store, Continuous Deployment, Data Preprocessing, Forecasting
Duke University
Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Unit Testing, Responsible AI, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis
Skills you'll gain: Model Evaluation, Model Deployment, Model Training, Model Optimization, Data Preprocessing, MLOps (Machine Learning Operations), Data Cleansing, Microservices, Data Pipelines, Feature Engineering, Data Quality, Containerization, Application Deployment, Service Level, Extract, Transform, Load, Data Transformation, System Monitoring, Machine Learning Methods, Performance Tuning, Machine Learning Algorithms
Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning
Pragmatic AI Labs
Skills you'll gain: MLOps (Machine Learning Operations), Databricks, Apache Spark, Model Evaluation, Hugging Face, Data Architecture, Recurrent Neural Networks (RNNs), LLM Application, Data Science, Data Mining, Mathematical Modeling, Scala Programming, Continuous Monitoring, Rust (Programming Language), Lean Six Sigma, Statistical Inference, Artificial Intelligence, Functional Testing, Exploratory Data Analysis, Programming Principles
Duke University
Skills you'll gain: MLOps (Machine Learning Operations), Data Management, Model Training, Data Quality, Model Deployment, Data Preprocessing, Application Lifecycle Management, Technical Management, Applied Machine Learning, Project Management, Machine Learning, Data Cleansing, Model Evaluation, Data Pipelines, Technical Design, Software Development Methodologies, Technology Solutions, Systems Design, Data Collection, Data Science
What brings you to Coursera today?
Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), Regression Testing, Kubernetes, Docker (Software), Feature Engineering, Containerization, Software Documentation, Data Pipelines, Git (Version Control System), Apache Airflow, Technical Documentation, Microservices, CI/CD, Unit Testing, API Design, Performance Metric, Python Programming, Version Control, Verification And Validation
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Software Documentation, Code Reusability, Model Training, Test Script Development, Continuous Delivery, Test Automation, Model Evaluation, Continuous Integration, Technical Documentation, API Design, Application Programming Interface (API), Data Validation, Applied Machine Learning, Machine Learning Methods, Maintainability, Version Control, Package and Software Management, Code Review
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Microservices, Containerization, Application Deployment, Service Level, Debugging, Unit Testing, Software Testing, System Monitoring, Continuous Deployment, Docker (Software), Software Architecture, Kubernetes, Software Design, Restful API, Systems Architecture, Cloud Computing Architecture, Application Performance Management, Continuous Monitoring
Skills you'll gain: Pandas (Python Package), Matplotlib, NumPy, Embeddings, Statistical Visualization, Machine Learning Algorithms, Natural Language Processing, Applied Machine Learning, Data Manipulation, Model Optimization, Machine Learning Methods, Pivot Tables And Charts, Linear Algebra, Deep Learning, Text Mining, Classification Algorithms, Markov Model, Unsupervised Learning, Data Preprocessing, Python Programming
Amazon Web Services
Skills you'll gain: Feasibility Studies, Business Analysis, Decision Making, Strategic Decision-Making, Business Planning, Data-Driven Decision-Making, Machine Learning, Strategic Thinking, AI Product Strategy, Business Leadership, Strategic Leadership, Project Planning
Skills you'll gain: Tensorflow, Model Optimization, Keras (Neural Network Library), Model Training, MLOps (Machine Learning Operations), Data Pipelines, Performance Tuning, Data Preprocessing
In summary, here are 10 of our most popular workflow of machine learning projects courses
- Machine Learning Operations (MLOps) on Google Cloud: Google Cloud
- MLOps | Machine Learning Operations: Duke University
- Machine Learning Made Easy for Software Engineers: Coursera
- Machine Learning and Deep Learning for Software Engineers: Board Infinity
- Machine Learning with Databricks and MLflow: Pragmatic AI Labs
- Managing Machine Learning Projects: Duke University
- Gradient to Production: MLOps & Model Serving: Coursera
- Production ML Engineering: Packaging, APIs, and Testing: Coursera
- Deploying and Debugging ML Microservices: Coursera
- Natural Language Processing with Real-World Projects: Packt
