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  • Ai And Machine Learning

Results for "AI and Machine Learning"


  • D

    Duke University

    Introduction to Machine Learning

    Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Transfer Learning, Reinforcement Learning, Convolutional Neural Networks, Deep Learning, Image Analysis, Applied Machine Learning, Natural Language Processing, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.8K reviews

    Intermediate · Course · 1 - 3 Months

  • D

    DeepLearning.AI

    Calculus for Machine Learning and Data Science

    Skills you'll gain: Applied Mathematics, Calculus, Numerical Analysis, Mathematical Modeling, Machine Learning, Python Programming, Artificial Neural Networks, Deep Learning, Visualization (Computer Graphics), Derivatives

    4.8
    Rating, 4.8 out of 5 stars
    ·
    951 reviews

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of London

    Machine Learning for All

    Skills you'll gain: Data Preprocessing, Machine Learning, Artificial Intelligence, Model Evaluation, Data Analysis, Image Analysis, Data Collection, Classification Algorithms

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • N

    National Taiwan University

    機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

    Skills you'll gain: Supervised Learning, Machine Learning, Statistical Machine Learning, Model Evaluation, Logistic Regression, Theoretical Computer Science, Classification Algorithms, Mathematical Theory & Analysis, Probability & Statistics, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    937 reviews

    Beginner · Course · 1 - 3 Months

  • P

    Packt

    Applied Machine Learning and Model Optimization

    Skills you'll gain: Supervised Learning, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Algorithms, Predictive Modeling, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Performance Tuning

    Advanced · Course · 1 - 3 Months

  • P

    Packt

    AI & Python Development Megaclass

    Skills you'll gain: Supervised Learning, Feature Engineering, Applied Machine Learning, Object Oriented Programming (OOP), Unsupervised Learning, Model Evaluation, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Transfer Learning, Machine Learning Algorithms, Data Visualization, Natural Language Processing, Seaborn, Predictive Modeling, Flask (Web Framework), Python Programming, Deep Learning, PyTorch (Machine Learning Library), Programming Principles, Web Applications

    Beginner · Specialization · 3 - 6 Months

  • C

    Coursera

    Advancing Your Career in AI and Machine Learning Engineering

    Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Technical Communication, Technical Documentation, MLOps (Machine Learning Operations), Model Deployment, Data Pipelines, Cloud Deployment, System Monitoring

    Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Generative AI: Introduction and Applications

    Skills you'll gain: Generative AI, ChatGPT, Real Time Data, Artificial Intelligence and Machine Learning (AI/ML), AI Personalization, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.2K reviews

    Beginner · Course · 1 - 4 Weeks

  • 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

  • M

    Microsoft

    Data Analytics and Machine Learning for Big Data

    Skills you'll gain: Apache Spark, MLOps (Machine Learning Operations), Large Language Modeling, Keras (Neural Network Library)

    Intermediate · Course · 1 - 3 Months

  • Status: Trending in AI
    Trending in AI
    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

  • I

    IBM

    Machine Learning Introduction for Everyone

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning, Supervised Learning, Applied Machine Learning, Data Science, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    308 reviews

    Beginner · Course · 1 - 4 Weeks

1234…834

In summary, here are 10 of our most popular AI and Machine Learning courses

  • Introduction to Machine Learning: Duke University
  • Calculus for Machine Learning and Data Science: DeepLearning.AI
  • Machine Learning for All: University of London
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
  • Applied Machine Learning and Model Optimization: Packt
  • AI & Python Development Megaclass: Packt
  • Advancing Your Career in AI and Machine Learning Engineering: Coursera
  • Generative AI: Introduction and Applications: IBM
  • Machine Learning: Algorithms in the Real World: Alberta Machine Intelligence Institute
  • Data Analytics and Machine Learning for Big Data: Microsoft

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