Results for "random+forest"
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: Descriptive Statistics, A/B Testing, Classification And Regression Tree (CART), Dashboard, Dashboard Creation, Model Evaluation, Model Deployment, Data-Driven Decision-Making, Risk Analysis, Histogram, Statistical Inference, Descriptive Analytics, Simulations, Predictive Modeling, Regression Analysis, Data Visualization, MLOps (Machine Learning Operations), Decision Making, Decision Tree Learning, Keras (Neural Network Library)
Skills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Machine Learning Algorithms, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, Plot (Graphics), Probability & Statistics, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, Model Evaluation, R Programming, Python Programming, Data Preprocessing, Applied Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML)
Skills 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, Data Access, Apache, Python Programming
Skills you'll gain: Model Evaluation, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Applied Machine Learning, Model Optimization, Model Training, Data Processing, Machine Learning Methods, Decision Tree Learning, Machine Learning Algorithms, Classification Algorithms, Analysis, Python Programming
Vanderbilt University
Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, AI powered creativity, Ideation, Verification And Validation, LLM Application, AI literacy, Multimodal Prompts, Responsible AI, AI Enablement, Data Visualization, Generative AI, Risking, Artificial Intelligence, Large Language Modeling, Plot (Graphics), Data Presentation, Statistical Visualization, File Management
What brings you to Coursera today?
Skills you'll gain: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), Service Level Agreement, Performance Stress Testing, Performance Measurement, Performance Analysis
Skills you'll gain: Matplotlib, Random Forest Algorithm, Predictive Modeling, Predictive Analytics, Machine Learning Algorithms, Plot (Graphics), Data Visualization, Data Preprocessing, Machine Learning, Programming Principles, Data Manipulation, Data Cleansing, Data Transformation, Supervised Learning, Python Programming, Data Science, Model Training, Decision Tree Learning, NumPy, Pandas (Python Package)
Skills you'll gain: Git (Version Control System), Model Training, Version Control, AI Workflows, Jupyter, Memory Management, Package and Software Management, Resource Utilization, Virtual Environment
Skills you'll gain: Apache Kafka, Apache Hadoop, Apache Spark, Real Time Data, Scala Programming, Data Integration, Command-Line Interface, Apache Hive, Big Data, Applied Machine Learning, Data Processing, System Design and Implementation, Apache Cassandra, Data Pipelines, Java, Distributed Computing, IntelliJ IDEA, Java Programming, Application Deployment, Enterprise Application Management
Skills you'll gain: Model Deployment, PyTorch (Machine Learning Library), Model Optimization, Recurrent Neural Networks (RNNs), Tensorflow, Artificial Intelligence, Model Training, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Application Deployment, Large Language Modeling, Text Mining, Artificial Neural Networks, Machine Learning, Natural Language Processing, Deep Learning, Predictive Modeling, Classification Algorithms, Time Series Analysis and Forecasting, Network Architecture
Packt
Skills you'll gain: Recurrent Neural Networks (RNNs), Model Evaluation, AI Personalization, Data Manipulation, Apache Spark, Tensorflow, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Preprocessing, Machine Learning Methods, Data Wrangling, Natural Language Processing, AWS SageMaker, Scalability, Applied Machine Learning, Data Processing, Autoencoders, Data Cleansing, Dimensionality Reduction, Machine Learning
In summary, here are 10 of our most popular random+forest courses
- Train ML Models:Â Coursera
- Statistical Inference & Predictive Modeling Foundations:Â Coursera
- AI Machine Learning with R & Python Projects:Â EDUCBA
- Spark and Python for Big Data with PySpark:Â EDUCBA
- Python: Implement & Evaluate Random Forests for ML:Â EDUCBA
- Prompt Engineering:Â Vanderbilt University
- Deploy & Optimize ML Services Confidently:Â Coursera
- Machine Learning: Random Forest with Python from Scratch©: Packt
- Optimize ML Dev: Version, Reproduce, and Save:Â Coursera
- Big Data Foundations with Hadoop and Spark:Â Packt
