Results for "regularization to avoid overfitting"
Status: Free TrialMultiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing
Status: Free TrialImperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives
Status: NewStatus: Free TrialDartmouth College
Skills you'll gain: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Machine Learning, Machine Learning Algorithms, Classification Algorithms, Regression Analysis, Probability & Statistics, Linear Algebra
Status: NewStatus: Free TrialSkills you'll gain: Random Forest Algorithm, Decision Tree Learning, Data Preprocessing, Applied Machine Learning, Jupyter, Classification Algorithms, Java, Sampling (Statistics), Feature Engineering, Model Evaluation, Supervised Learning, Predictive Modeling, Machine Learning, Learning Styles, Program Evaluation, Program Implementation
Status: Free TrialDeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods
Status: NewStatus: Free TrialSkills you'll gain: Model Deployment, Scikit Learn (Machine Learning Library), Model Evaluation, Data Preprocessing, Large Language Modeling, Version Control
What brings you to Coursera today?
Status: NewStatus: Free TrialSkills you'll gain: MLOps (Machine Learning Operations), Responsible AI, CI/CD, Model Deployment, Continuous Integration, Continuous Delivery, Continuous Deployment, Cloud Platforms, Model Evaluation, Automation, Data Governance, Performance Tuning, Continuous Monitoring, Performance Analysis, Scalability
Status: NewStatus: Free TrialSkills you'll gain: Data Preprocessing, Data Pipelines, Java, Data Processing, Feature Engineering, Data Cleansing, Data Quality, Data Transformation, Data Validation, Data Access, Continuous Monitoring, Unit Testing, Object Oriented Programming (OOP)
Status: NewStatus: Free TrialSkills you'll gain: Capacity Planning, Capacity Management, Data-Driven Decision-Making, Resource Planning, Resource Allocation, Project Coordination, Project Management, Resource Management, Performance Measurement, Business Communication, Risk Mitigation, Data Visualization, Spreadsheet Software, Stakeholder Communications
Status: NewStatus: Free TrialSkills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Containerization, Performance Tuning, Docker (Software), Java, Application Performance Management, Artificial Intelligence and Machine Learning (AI/ML), Analysis, Data Structures
Status: NewStatus: Free TrialSkills you'll gain: Data Structures, Feature Engineering, MLOps (Machine Learning Operations), Java, Performance Tuning, Data Processing, Applied Machine Learning, System Monitoring, Scalability, Performance Analysis, Performance Testing, Tree Maps, Benchmarking, Graph Theory, Program Implementation
Status: NewSkills you'll gain: Generative AI
What brings you to Coursera today?
In summary, here are 10 of our most popular regularization to avoid overfitting courses
- Machine Learning:Â DeepLearning.AI
- Mathematics for Machine Learning:Â Imperial College London
- Machine Learning Fundamentals:Â Dartmouth College
- Improve Accuracy with ML Ensemble Methods:Â Coursera
- Mathematics for Machine Learning and Data Science:Â DeepLearning.AI
- Optimize AI: Build Reusable Model Pipelines:Â Coursera
- Automate, Validate, and Promote ML Models Safely:Â Coursera
- Parse & Normalize Data for ML Pipelines:Â Coursera
- Analyze and Mitigate Project Resource Overloads:Â Coursera
- Optimize Java Memory for ML Performance:Â Coursera
