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Cours en Apprentissage automatique

Les cours en apprentissage automatique peuvent vous aider à comprendre comment construire, entraîner et analyser des modèles prédictifs. Vous pouvez développer des compétences en préparation des données, choix d'algorithmes, optimisation et évaluation. De nombreux cours utilisent des bibliothèques courantes pour tester des modèles.


Cours et certificats populaires en Apprentissage automatique


  • Status: Preview
    Preview
    H

    H2O.ai

    Practical Machine Learning on H2O

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Deep Learning, Machine Learning Methods, Autoencoders, Anomaly Detection, Machine Learning Algorithms, Applied Machine Learning, Model Training, Machine Learning, Machine Learning Software, Supervised Learning, Decision Tree Learning, Predictive Modeling, Data Validation, Classification Algorithms, Random Forest Algorithm, Data Import/Export, Model Optimization, Data Manipulation

    4.5
    Rating, 4.5 out of 5 stars
    ·
    74 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    C

    Coursera

    Machine Learning in Retail

    Skills you'll gain: Customer Analysis, Unsupervised Learning, Customer Insights, Marketing Analytics, Applied Machine Learning, Data Analysis, Machine Learning Methods, Web Analytics, Data-Driven Marketing, Retail Store Operations, Machine Learning, Machine Learning Algorithms, Histogram, Decision Tree Learning, Data Preprocessing, Pandas (Python Package)

    4.9
    Rating, 4.9 out of 5 stars
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    9 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDHEC Business School

    Python and Machine Learning for Asset Management

    Skills you'll gain: Investment Management, Portfolio Management, Asset Management, Investments, Portfolio Risk, Machine Learning Methods, Machine Learning, Statistical Machine Learning, Applied Machine Learning, Financial Modeling, Supervised Learning, Model Evaluation, Predictive Analytics, Market Data, Feature Engineering, Unsupervised Learning, Regression Analysis, Statistical Methods, Analysis, Computer Science

    3.1
    Rating, 3.1 out of 5 stars
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    332 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Deep Learning & Neural Networks with Keras

    Skills you'll gain: Keras (Neural Network Library), Deep Learning, Transfer Learning, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Model Optimization, Machine Learning Methods, Image Analysis, Applied Machine Learning, Autoencoders, Model Training, Regression Analysis, Network Architecture, Natural Language Processing, Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.1K reviews

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Build a Machine Learning Web App with Streamlit and Python

    Skills you'll gain: Machine Learning Algorithms, Dashboard Creation, Classification Algorithms, Interactive Data Visualization, Data Visualization Software, Model Evaluation, Applied Machine Learning, Machine Learning, Scikit Learn (Machine Learning Library), Plot (Graphics), Web Applications, Logistic Regression, Predictive Modeling, Model Training, Data Science, Python Programming, Fine-tuning, Model Optimization, Pandas (Python Package)

    4.7
    Rating, 4.7 out of 5 stars
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    417 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with Python: Case Studies

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Feature Engineering, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Model Training, Risk Modeling, Predictive Modeling, Statistical Methods, Predictive Analytics, Credit Risk, Supervised Learning, Statistical Modeling, Unsupervised Learning, Machine Learning Methods, Machine Learning, Python Programming, Logistic Regression

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Cloud Machine Learning Engineering and MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), Continuous Delivery, Applied Machine Learning, Cloud Engineering, Google Cloud Platform, Model Deployment, Cloud Applications, Cloud Development, Cloud API, Cloud Deployment, Artificial Intelligence, Machine Learning, Microsoft Azure, AI Workflows, Software Engineering, Computer Vision, Application Programming Interface (API), Natural Language Processing, Flask (Web Framework)

    4.5
    Rating, 4.5 out of 5 stars
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    92 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    N

    Northeastern University

    Machine Learning with Small Data Part 1

    Skills you'll gain: Transfer Learning, Small Data, Deep Learning, Applied Machine Learning, Machine Learning Methods, Model Training, Unsupervised Learning, Machine Learning, Data Synthesis, Supervised Learning

    Mixed · Course · 1 - 3 Months

  • C

    Coursera

    Interpretable Machine Learning Applications: Part 2

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Data Preprocessing, Classification Algorithms, Random Forest Algorithm, Data Transformation, Machine Learning Methods, Model Training, Predictive Modeling, Regression Analysis, Feature Engineering, Decision Tree Learning, Machine Learning, Exploratory Data Analysis, Performance Measurement

    4.3
    Rating, 4.3 out of 5 stars
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    28 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    I

    IBM

    Deep Learning and Reinforcement Learning

    Skills you'll gain: Autoencoders, Generative AI, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Unsupervised Learning, Machine Learning Methods, Transfer Learning, Model Optimization, Image Analysis, Artificial Neural Networks, Keras (Neural Network Library), Fine-tuning, Machine Learning, Artificial Intelligence, Computer Vision

    4.6
    Rating, 4.6 out of 5 stars
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    297 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Deploying Machine Learning Models

    Skills you'll gain: Model Deployment, Data Manipulation, MLOps (Machine Learning Operations), Web Frameworks, Model Evaluation, Applied Machine Learning, Flask (Web Framework), Data Preprocessing, Django (Web Framework), Web Applications, Model Optimization, Data Cleansing, AI Personalization, Predictive Modeling, Machine Learning, Machine Learning Algorithms, Python Programming

    3.6
    Rating, 3.6 out of 5 stars
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    54 reviews

    Mixed · Course · 1 - 3 Months

  • C

    Coursera

    Interpretable Machine Learning Applications: Part 4

    Skills you'll gain: Predictive Modeling, Applied Machine Learning, Data Preprocessing, Data Analysis, Data Import/Export, Google Cloud Platform, Model Evaluation, Decision Tree Learning, Model Training, Data Processing, Analysis, Machine Learning, Classification Algorithms, Machine Learning Methods, Random Forest Algorithm, Statistical Visualization, Software Visualization

    4.7
    Rating, 4.7 out of 5 stars
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    23 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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

  • Practical Machine Learning on H2O: H2O.ai
  • Machine Learning in Retail: Coursera
  • Python and Machine Learning for Asset Management : EDHEC Business School
  • Introduction to Deep Learning & Neural Networks with Keras: IBM
  • Build a Machine Learning Web App with Streamlit and Python: Coursera
  • Machine Learning with Python: Case Studies: EDUCBA
  • Cloud Machine Learning Engineering and MLOps: Duke University
  • Machine Learning with Small Data Part 1: Northeastern University
  • Interpretable Machine Learning Applications: Part 2: Coursera
  • Deep Learning and Reinforcement Learning: IBM

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