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Results for "random+forests"
Skills you'll gain: Supervised Learning, Feature Engineering, Jupyter, Unsupervised Learning, Scikit Learn (Machine Learning Library), Python Programming, Predictive Modeling, Machine Learning, Dimensionality Reduction, Classification And Regression Tree (CART), Matplotlib, NumPy, Regression Analysis, Statistical Modeling
Google Cloud
Skills you'll gain: Feature Engineering, Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), MLOps (Machine Learning Operations), Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Dataflow, Cloud Platforms, Data Management, Data Governance, Workflow Management, Application Deployment, Deep Learning, Applied Machine Learning, Machine Learning, Predictive Modeling
DeepLearning.AI
Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Unsupervised Learning, Statistical Modeling
Stanford University
Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Statistical Modeling, Bayesian Statistics, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Statistical Inference, Sampling (Statistics), Statistical Methods, Natural Language Processing, Algorithms, Computational Thinking
Skills you'll gain: Matplotlib, Data Visualization, Deep Learning, Linear Algebra, Artificial Neural Networks, NumPy, Image Analysis, Keras (Neural Network Library), Seaborn, Pandas (Python Package), Tensorflow, Machine Learning, Applied Machine Learning, Computer Vision, Artificial Intelligence and Machine Learning (AI/ML), Scikit Learn (Machine Learning Library), Supervised Learning, Python Programming, Jupyter, Machine Learning Methods
Skills you'll gain: Microsoft Azure, Unsupervised Learning, Databricks, MLOps (Machine Learning Operations), Applied Machine Learning, Regression Analysis, Scikit Learn (Machine Learning Library), Predictive Modeling, Cloud Management, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Virtual Machines, Application Deployment, Data Pipelines, Data Transformation
What brings you to Coursera today?
Skills you'll gain: Microsoft Azure, MLOps (Machine Learning Operations), Databricks, Cloud Computing, Applied Machine Learning, Data Ethics, Data Pipelines, Machine Learning, Tensorflow, Continuous Monitoring, Scalability
DeepLearning.AI
Skills you'll gain: Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization
University of Michigan
Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Dimensionality Reduction, Random Forest Algorithm
Skills you'll gain: Apache Spark, PySpark, Applied Machine Learning, Big Data, Machine Learning Methods, Data Storage, Data Pipelines, Machine Learning Algorithms, Distributed Computing, Data Processing, Exploratory Data Analysis, Statistical Analysis
Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Scikit Learn (Machine Learning Library), Data Processing, Data Cleansing, Machine Learning, Regression Analysis, Data Manipulation, Business Analytics, Feature Engineering, Random Forest Algorithm, Statistical Modeling, Sampling (Statistics), Performance Metric
In summary, here are 10 of our most popular random+forests courses
- Machine Learning with Python: IBM
- Machine Learning on Google Cloud: Google Cloud
- Supervised Machine Learning: Regression and Classification : DeepLearning.AI
- Probabilistic Graphical Models: Stanford University
- Deep Learning with Real-World Projects: Packt
- Microsoft Azure Machine Learning for Data Scientists: Microsoft
- Build and Operate Machine Learning Solutions with Azure: Microsoft
- Advanced Learning Algorithms: DeepLearning.AI
- Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
- Applied Machine Learning in Python: University of Michigan
