Results for "random+forests"
Status: Free TrialSkills you'll gain: PySpark, Apache Spark, Model Evaluation, MySQL, Data Pipelines, Scala Programming, Extract, Transform, Load, Logistic Regression, Customer Analysis, Apache Hadoop, Predictive Modeling, Applied Machine Learning, Data Processing, Data Persistence, Advanced Analytics, Big Data, Apache Maven, Unsupervised Learning, Apache, Python Programming
Status: NewStatus: Free TrialSkills you'll gain: Predictive Modeling, Model Evaluation, Data Visualization, Statistical Analysis, Predictive Analytics, Feature Engineering, Data Mining, Statistical Modeling, Risk Modeling, R Programming, Data Manipulation, Business Analytics, Data Analysis, Decision Tree Learning, Data Preprocessing, Data Cleansing, Probability & Statistics, Transaction Processing, Applied Machine Learning, Machine Learning
Status: NewStatus: Preview
Status: NewStatus: Free TrialSkills you'll gain: Descriptive Statistics, A/B Testing, Classification And Regression Tree (CART), Dashboard, Model Evaluation, Model Deployment, Data-Driven Decision-Making, Histogram, Data Presentation, Predictive Modeling, Data Storytelling, Exploratory Data Analysis, Risk Analysis, Risk Mitigation, Regression Analysis, Data Visualization, MLOps (Machine Learning Operations), Decision Tree Learning, Keras (Neural Network Library), Statistical Inference
Status: NewStatus: Free TrialSkills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, Model Evaluation, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Data Preprocessing, Linear Algebra, Applied Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML)
Status: PreviewSkills you'll gain: Model Evaluation, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Applied Machine Learning, Decision Tree Learning, Feature Engineering, Machine Learning Algorithms, Classification Algorithms, Predictive Modeling, Data Analysis, Python Programming
What brings you to Coursera today?
Status: Free TrialSkills you'll gain: Generative AI, Model Evaluation, Supervised Learning, Generative Model Architectures, Recurrent Neural Networks (RNNs), Unsupervised Learning, Data Preprocessing, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Generative Adversarial Networks (GANs), Retrieval-Augmented Generation, Data Collection, Machine Learning Algorithms, Convolutional Neural Networks, Model Deployment, Transfer Learning, Hugging Face
Status: NewStatus: Free TrialSkills you'll gain: Analytics, Big Data, Scalability, Responsible AI, Complex Problem Solving
Status: NewStatus: Free TrialSkills you'll gain: Predictive Analytics, MLOps (Machine Learning Operations), Verification And Validation, Data Preprocessing, Data Transformation, Exploratory Data Analysis, Data Manipulation, Statistical Reporting
Status: NewStatus: Free TrialCoursera
Skills you'll gain: Classification And Regression Tree (CART), Model Deployment, Decision Tree Learning, Predictive Modeling, Model Evaluation, Feature Engineering, Machine Learning Methods, Random Forest Algorithm, Applied Machine Learning, Performance Tuning, Statistical Machine Learning, Scikit Learn (Machine Learning Library), Performance Analysis
Status: NewStatus: Free TrialSkills you'll gain: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), DevOps, Service Level Agreement, API Design, Performance Measurement, Performance Analysis
Status: NewStatus: Free TrialSkills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Business Metrics, Feature Engineering, Predictive Modeling, Random Forest Algorithm, Supervised Learning, Machine Learning Methods, Scikit Learn (Machine Learning Library), Data Preprocessing, Applied Machine Learning, Classification And Regression Tree (CART), Performance Metric, Regression Analysis, Continuous Monitoring, Statistical Methods, Statistical Hypothesis Testing, Algorithms
In summary, here are 10 of our most popular random+forests courses
- Spark and Python for Big Data with PySpark:Â EDUCBA
- Apply R for Predictive Analytics and Machine Learning:Â EDUCBA
- Probabilistic Graphical Models: A Compact Introduction:Â Coursera
- Statistical Inference & Predictive Modeling Foundations:Â Coursera
- AI Machine Learning with R & Python Projects:Â EDUCBA
- Python: Implement & Evaluate Random Forests for ML:Â EDUCBA
- Machine Learning with Scikit-learn, PyTorch & Hugging Face:Â Coursera
- Analyze and Apply Generative AI in Research & Development:Â EDUCBA
- Optimize Vision Datasets: Augment and Analyze:Â Coursera
- Grow Trees & Powerful Ensembles:Â Coursera
