Results for "supervised learning process"
Coursera
Skills you'll gain: Random Forest Algorithm, Model Evaluation, Feature Engineering, Model Training, Applied Machine Learning, Supervised Learning, Geospatial Mapping, Predictive Modeling, Image Analysis, Verification And Validation, Data Science, Environmental Engineering
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
Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Business Metrics, Model Training, Feature Engineering, Predictive Modeling, Random Forest Algorithm, Supervised Learning, Scikit Learn (Machine Learning Library), Performance Metric, Machine Learning Algorithms, Regression Analysis, Continuous Monitoring, Statistical Methods
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
Skills you'll gain: Exploratory Data Analysis, Autoencoders, Feature Engineering, Unsupervised Learning, Supervised Learning, Generative AI, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Science, Machine Learning, Python Programming
What brings you to Coursera today?
Coursera
Skills you'll gain: MLOps (Machine Learning Operations), Data Pipelines, Model Evaluation, Systems Design, Transfer Learning, Data Preprocessing, Data Quality, Feature Engineering, Deep Learning, Python Programming, Data Validation, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Software Engineering, Debugging, Supervised Learning, Git (Version Control System), Performance Metric, Statistical Analysis
Skills you'll gain: Classification Algorithms, Supervised Learning, Model Evaluation, Data Preprocessing, Logistic Regression, Machine Learning Algorithms, Decision Tree Learning, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Business Logic, Machine Learning Methods, Scikit Learn (Machine Learning Library), Data Cleansing, Machine Learning, Regression Analysis, Random Forest Algorithm, Model Optimization, Sampling (Statistics)
Alberta Machine Intelligence Institute
Skills you'll gain: Supervised Learning, Model Optimization, Machine Learning Algorithms, Machine Learning Methods, Applied Machine Learning, Classification Algorithms, Model Evaluation, Jupyter, Statistical Machine Learning, Decision Tree Learning, Model Training, Machine Learning, Data Preprocessing, Business Solutions, Python Programming, Regression Analysis, Performance Analysis, Data Processing
DeepLearning.AI
Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, Model Training, NumPy, Machine Learning Algorithms, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Model Optimization, Regression Analysis, Algorithms
Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Machine Learning Methods, Statistical Hypothesis Testing, Model Training, Data Processing, Data Access, Scikit Learn (Machine Learning Library), Machine Learning
Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, Model Optimization, Model Training, Workflow Management, Predictive Modeling
In summary, here are 10 of our most popular supervised learning process courses
- Train ML Models: Coursera
- Gradient to Production: MLOps & Model Serving: Coursera
- Machine Learning: DeepLearning.AI
- Build Predictive & Supervised Models: Coursera
- Machine Learning Operations (MLOps) on Google Cloud: Google Cloud
- IBM Machine Learning: IBM
- ML Model Training & Validation: Coursera
- Supervised Machine Learning: Classification: IBM
- Machine Learning Algorithms: Supervised Learning Tip to Tail: Alberta Machine Intelligence Institute
- Supervised Machine Learning: Regression and Classification : DeepLearning.AI
