Results for "optimization techniques for machine learning"
Multiple 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
Imperial 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
Skills you'll gain: Tensorflow, Keras (Neural Network Library), MLOps (Machine Learning Operations), Data Pipelines, Performance Tuning
DeepLearning.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, Mathematical Modeling, Data Preprocessing, Machine Learning, Machine Learning Methods
University of Pennsylvania
Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Agentic systems, Artificial Intelligence, Artificial Neural Networks, Algorithms, Python Programming
Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Random Forest Algorithm, Data Analysis, Predictive Modeling, Model Evaluation, Bayesian Network, Python Programming, Statistical Modeling, Classification Algorithms
What brings you to Coursera today?
Alberta Machine Intelligence Institute
Skills you'll gain: Supervised Learning, Data Preprocessing, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Model Evaluation, Data Quality, Classification Algorithms, MLOps (Machine Learning Operations), Model Deployment, Jupyter, Data Validation, Machine Learning, Decision Tree Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Project Management
Google Cloud
Skills you'll gain: Feature Engineering, Generative AI, Model Deployment, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Machine Learning, Data Preprocessing, MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, AI Enablement, Prompt Engineering, Cloud Deployment, Supervised Learning, Scikit Learn (Machine Learning Library), AI Workflows, Cloud Computing
Coursera
Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling
Skills you'll gain: Model Evaluation, Model Deployment, Data Preprocessing, MLOps (Machine Learning Operations), Data Cleansing, Microservices, Data Pipelines, Feature Engineering, Data Quality, Data Validation, Containerization, Application Deployment, Extract, Transform, Load, Data Transformation, System Monitoring, Debugging, Applied Machine Learning, Machine Learning Methods, Performance Tuning, Machine Learning Algorithms
DeepLearning.AI
Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Regression Analysis, Unsupervised Learning
Coursera
Skills you'll gain: Apache Airflow, MLOps (Machine Learning Operations), User Acceptance Testing (UAT), Prompt Patterns, LLM Application, AI Security, Extract, Transform, Load, Scripting, Technical Communication, SQL, Data Pipelines, PyTorch (Machine Learning Library), Miro AI, Data Presentation, Large Language Modeling, Python Programming, Performance Tuning, Root Cause Analysis, Statistical Analysis, Version Control
In summary, here are 10 of our most popular optimization techniques for machine learning courses
- Machine Learning: DeepLearning.AI
- Mathematics for Machine Learning: Imperial College London
- Build & Optimize TensorFlow ML Workflows: Coursera
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- AI and Machine Learning Essentials with Python: University of Pennsylvania
- The Nuts and Bolts of Machine Learning: Google
- Machine Learning: Algorithms in the Real World: Alberta Machine Intelligence Institute
- Machine Learning on Google Cloud: Google Cloud
- Foundations of Machine Learning: Coursera
- Machine Learning Made Easy for Software Engineers: Coursera
