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vijay kumari
How does Deep Learning differ from Machine Learning?
By vijay kumari in Blockchain onJul 22 2019
  • Rohit Gupta
    Jul, 2019 30

    Machine Learning can be defined as :

    A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E

    Deep Learning can be defined as:

    Deep learning is a particular kind of machine learning that achieves great power and flexibility by learning to represent the world as a nested hierarchy of concepts, with each concept defined in relation to simpler concepts, and more abstract representations computed in terms of less abstract ones.

    From the above definitions, it can be inferred that Deep Learning is a sub-branch of Machine Learning. Also, deep learning alogos are used to provide a greater understanding of data and also to get a more accurate model, i.e. Deep Learning comes into picture when the traditional Machine Learning alogos fail to provide the desired results.

    Deep Learning is used in scenarios where high-end calculations are needed i.e. the amount of data is huge for the traditional ML alogos to handle and process.

    Machine Learning finds its usage in providing the base for deep learning to work

    ML Algorithms

    1. Linear Regression
    2. Logistic Regression
    3. Random Forest
    4. Decision Tree
    5. Support Vector Machine

    DL Algorithms

    1. Neural Networks
    2. RCNN
    3. CNN
    4. ResNET

    • 2

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