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  • Optimization Techniques For Machine Learning

Results for "optimization techniques for machine learning"


  • D
    S

    Multiple educators

    Machine Learning

    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

    4.9
    Rating, 4.9 out of 5 stars
    ·
    38K reviews

    Beginner · Specialization · 1 - 3 Months

  • I

    Imperial College London

    Mathematics for Machine Learning

    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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15K reviews

    Beginner · Specialization · 3 - 6 Months

  • C

    Coursera

    Optimize and Deploy Edge AI Models

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Optimize AI: Build Fast Efficient Pipelines

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Optimize ML Dev: Version, Reproduce, and Save

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Build & Optimize TensorFlow ML Workflows

    Intermediate · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.2K reviews

    Intermediate · Specialization · 1 - 3 Months

  • U

    University of Pennsylvania

    AI and Machine Learning Essentials with Python

    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

    4.5
    Rating, 4.5 out of 5 stars
    ·
    44 reviews

    Intermediate · Specialization · 3 - 6 Months

  • A

    Alberta Machine Intelligence Institute

    Machine Learning: Algorithms in the Real World

    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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.1K reviews

    Intermediate · Specialization · 3 - 6 Months

  • D

    Dartmouth College

    Practical Machine Learning: Foundations to Neural Networks

    Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Classification Algorithms, Statistical Inference

    Build toward a degree

    Intermediate · Specialization · 3 - 6 Months

  • C

    Coursera

    Foundations of Machine Learning

    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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    11 reviews

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    AI Techniques, Causal Inference & Business Optimization

    Skills you'll gain: Data Ethics, Responsible AI, Retrieval-Augmented Generation, LLM Application, Operations Research, Strategic Thinking, Strategic Decision-Making, Business Strategy, Apache Kafka, Stakeholder Communications, Large Language Modeling, Real Time Data, AI Enablement, Performance Testing, Prompt Engineering, Business Analytics, Reinforcement Learning, Inventory Management System, Stakeholder Analysis, General Data Protection Regulation (GDPR)

    Intermediate · Specialization · 3 - 6 Months

1234…834

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
  • Optimize and Deploy Edge AI Models: Coursera
  • Optimize AI: Build Fast Efficient Pipelines: Coursera
  • Optimize ML Dev: Version, Reproduce, and Save: Coursera
  • 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
  • Machine Learning: Algorithms in the Real World: Alberta Machine Intelligence Institute
  • Practical Machine Learning: Foundations to Neural Networks: Dartmouth College

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