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  • Fundamental Concepts In Machine Learning

Results for "fundamental concepts in machine learning"


  • Status: New
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    P

    Pearson

    Learning Deep Learning: Unit 1

    Skills you'll gain: Deep Learning, PyTorch (Machine Learning Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Large Language Modeling, Machine Learning, Python Programming, Algorithms, Network Architecture, Data Processing

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    A

    Alberta Machine Intelligence Institute

    Introduction to Applied Machine Learning

    Skills you'll gain: Data Ethics, Applied Machine Learning, Data Processing, Machine Learning, Machine Learning Algorithms, Product Lifecycle Management, Supervised Learning, Business Requirements, Data Quality, Business Analysis, Unsupervised Learning, Artificial Intelligence, Performance Metric

    4.7
    Rating, 4.7 out of 5 stars
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    746 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    IBM

    Unsupervised Machine Learning

    Skills you'll gain: Unsupervised Learning, Dimensionality Reduction, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Feature Engineering, Machine Learning, Statistical Machine Learning, Text Mining, Data Mining, Data Science, Big Data, NumPy, Data Analysis, Algorithms, Natural Language Processing, Linear Algebra

    4.7
    Rating, 4.7 out of 5 stars
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    352 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
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    SAS

    Four Rare Machine Learning Skills All Data Scientists Need

    Skills you'll gain: Predictive Modeling, Predictive Analytics, Marketing Analytics, Statistical Machine Learning, Machine Learning, Data Science, Supervised Learning, Applied Machine Learning, Marketing, Statistical Analysis

    4.7
    Rating, 4.7 out of 5 stars
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    9 reviews

    Advanced · Course · 1 - 4 Weeks

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    J

    Johns Hopkins University

    Introduction to AI: Key Concepts and Applications

    Skills you'll gain: Performance Metric, Artificial Intelligence, Strategic Leadership, Responsible AI, Strategic Decision-Making, Data Quality, MLOps (Machine Learning Operations), Applied Machine Learning, Machine Learning, Algorithms, Artificial Neural Networks, Data Validation, Decision Tree Learning, Random Forest Algorithm, Resource Utilization, System Requirements

    4.8
    Rating, 4.8 out of 5 stars
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    23 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    Whizlabs

    AWS: Machine Learning & MLOps Foundations

    Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Predictive Modeling, Applied Machine Learning, Data Processing, Regression Analysis, Machine Learning, Supervised Learning, Feature Engineering, Data Cleansing, Continuous Deployment, Unsupervised Learning

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    W

    Whizlabs

    NVIDIA: Fundamentals of Deep Learning

    Skills you'll gain: Deep Learning, Image Analysis, Computer Vision, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Tensorflow, Applied Machine Learning, Machine Learning, Supervised Learning, Machine Learning Algorithms, Data Processing, Linear Algebra, Network Architecture

    4.4
    Rating, 4.4 out of 5 stars
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    8 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
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    N

    Northeastern University

    Machine Learning in Healthcare: Fundamentals & Applications

    Skills you'll gain: Data Mining, Health Informatics, Big Data, Applied Machine Learning, Predictive Modeling, Machine Learning, Artificial Intelligence, Random Forest Algorithm, Clinical Practices, Responsible AI, Deep Learning, Health Care, Unsupervised Learning, Algorithms, Data Cleansing, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
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    8 reviews

    Beginner · Course · 1 - 4 Weeks

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    E

    EDUCBA

    Master Machine Learning with TensorFlow: Basics to Advanced

    Skills you'll gain: Tensorflow, Scikit Learn (Machine Learning Library), Machine Learning, Feature Engineering, Deep Learning, Matplotlib, Jupyter, Python Programming, Data Processing, NumPy, Data Cleansing, Image Analysis, Artificial Neural Networks, Seaborn, Development Environment, Pandas (Python Package), Regression Analysis

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
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    S

    SAS

    Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls

    Skills you'll gain: Responsible AI, Machine Learning, Data Ethics, Predictive Analytics, Statistical Modeling, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Science, Machine Learning Algorithms, Decision Tree Learning, Data Analysis, Regression Analysis, Performance Analysis, Deep Learning, Artificial Neural Networks

    4.9
    Rating, 4.9 out of 5 stars
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    64 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
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    National Taiwan University

    機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

    Skills you'll gain: Supervised Learning, Machine Learning, Machine Learning Algorithms, Data Validation, Classification And Regression Tree (CART), Algorithms, Regression Analysis, Predictive Modeling, Feature Engineering, Artificial Intelligence, Data Ethics, Statistical Methods, Data Transformation

    4.9
    Rating, 4.9 out of 5 stars
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    331 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    U

    University of Pennsylvania

    AI Fundamentals for Non-Data Scientists

    Skills you'll gain: Generative AI, Data Management, Big Data, Machine Learning Algorithms, Machine Learning, Tensorflow, Artificial Intelligence, Deep Learning, Algorithms, Process Optimization, Data Analysis, Artificial Neural Networks, Natural Language Processing

    4.8
    Rating, 4.8 out of 5 stars
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    927 reviews

    Mixed · Course · 1 - 3 Months

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In summary, here are 10 of our most popular fundamental concepts in machine learning courses

  • Learning Deep Learning: Unit 1: Pearson
  • Introduction to Applied Machine Learning: Alberta Machine Intelligence Institute
  • Unsupervised Machine Learning: IBM
  • Four Rare Machine Learning Skills All Data Scientists Need: SAS
  • Introduction to AI: Key Concepts and Applications: Johns Hopkins University
  • AWS: Machine Learning & MLOps Foundations: Whizlabs
  • NVIDIA: Fundamentals of Deep Learning: Whizlabs
  • Machine Learning in Healthcare: Fundamentals & Applications: Northeastern University
  • Master Machine Learning with TensorFlow: Basics to Advanced: EDUCBA
  • Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls: SAS

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