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Machine Learning

Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so.

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Python for data Analysis...

By : irfan Azmat

Hindi...

4 1170

2:5:34 hrs   14 lectures All Level   

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Learn Machine Learning...

By : Skillcart E-Learning

Learn to create Machine Learning Algorithms in Python and R from two Data Science exp...

4.4 818

1:10:59 hrs   14 lectures All Level   

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Data Science With Python...

By : Skillcart E-Learning

All about Data Science!...

4.3 627

1:18:3 hrs   18 lectures All Level   

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Machine Learning for Predictive Maps in Python and Leaflet...

By : Edwin Bomela

Using the power of machine learning to build predictive map applications...

4.6 833

3:44:45 hrs   32 lectures Intermedite Level   

javascript-course-for-beginner-to-expert-data-visualization

Introduction to Data Science for Complete Beginners...

By : Fahad Masood Reda

Most Frequent Questions about Data Science are answered in this course...

4.5 663

1:35:3 hrs   19 lectures All Level   

javascript-course-for-beginner-to-expert-data-visualization

Data Science and Machine Learning Basic to Advanced...

By : Raj Chhabria

Complete Introduction to Data Science and Machine Learning from Basic to Advanced....

4 827

4:22:11 hrs   36 lectures All Level   

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Building Big Data Pipelines with PySpark + MongoDB + Bokeh...

By : Edwin Bomela

Build intelligent data pipelines with big data processing and machine learning techno...

4 896

2:3:1 hrs   25 lectures All Level   

javascript-course-for-beginner-to-expert-data-visualization

Natural Language Processing - Zero to Hero with Python...

By : Rithesh Sreenivasan

Natural Language Processing : Basics to Advanced with practical implementation using ...

4 925

21 lectures All Level   

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Python for Data Science and Machine Learning...

By : Mohit Jain

Kick Start Your Data Science Career from Beginner to Master...

4 711

8:23:1 hrs   47 lectures All Level   

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Learn Data Science & Machine Learning with R from A-Z Course...

By : Juan Galvan

Become a professional Data Scientist with R and learn Machine Learning, Data Analysis...

4.1 7997

22:15:26 hrs   72 lectures All Level   

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Frequently asked questions
  • What is Machine Learning (ML)?

    Machine Learning is a branch of artificial intelligence that focuses on developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. ML allows systems to improve their performance over time based on experience.

  • How does Machine Learning work?

    Machine Learning works by training models on labeled data, allowing the algorithm to learn patterns and relationships. These trained models can then make predictions or decisions when presented with new, unseen data. The process involves training, testing, and iterating to improve the model's accuracy.

  • What are the types of Machine Learning?

    Types of ML include:
    Supervised Learning: Models learn from labeled data with input-output pairs.
    Unsupervised Learning: Models discover patterns and relationships in unlabeled data.
    Reinforcement Learning: Agents learn through interaction with an environment, receiving rewards or penalties based on actions.
    Semi-Supervised Learning and Self-Supervised Learning: Hybrid approaches using both labeled and unlabeled data.

  • What are common applications of Machine Learning?

    ML is used in various applications, including:
    Image and speech recognition
    Natural language processing
    Recommendation systems
    Fraud detection
    Predictive analytics
    Autonomous vehicles
    Healthcare diagnostics

  • How does Machine Learning use algorithms and models?

    Machine Learning algorithms process data and learn patterns to create models. These models, based on learned parameters, can then make predictions or decisions when presented with new data. Common algorithms include decision trees, neural networks, support vector machines, and clustering algorithms.

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