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Title: Best Machine Learning Course Online mumbai


1
NEAR LEARN
  • Machine Learning classroom training Mumbai

2
INTRODUCTION
3
What is Machine Learning?
  • Investigation of calculations that enhance their
    execution at some assignment with experience
  • Enhance an execution rule utilizing precedent
    information or past experience.
  • Job of Statistics Inference from an example
  • Job of Computer science Efficient calculations
    to
  • Take care of the improvement issue
  • Speaking to and assessing the model for deduction

4
Growth of Machine Learning
  • Machine learning is favoured way to deal with
  • Discourse acknowledgment, Natural dialect
    handling
  • PC vision
  • Therapeutic results investigation
  • Robot control
  • Computational science This incline is quickening
  • Enhanced machine learning calculations
  • Enhanced information catch, organizing, quicker
    PCs
  • Programming excessively mind boggling, making it
    impossible to compose by hand
  • New sensors/IO gadgets
  • Interest for self-customization to client,
    condition
  • It ends up being hard to extricate information
    from human experts?failure of master frameworks
    in the 1980's.

5
Applications
  • Association Analysis
  • Supervised Learning
  • Classification
  • Regression/Prediction
  • Unsupervised Learning
  • Reinforcement Learning

6
Supervised Learning
  • Prediction of future cases Use the rule to
    predict the output for future inputs
  • Knowledge extraction The rule is easy to
    understand
  • Compression The rule is simpler than the data it
    explains
  • Outlier detection Exceptions that are not
    covered by the rule, e.g., fraud
  • Supervised learning involve training data in
    which there is a desired output.

7
Unsupervised Learning
  • training data that doesnt have clear outputs.
  • Clustering Grouping similar instances
  • Other applications Summarization, Association
    Analysis
  • Example applications
  • Customer segmentation in CRM
  • Image compression Color quantization
  • Bioinformatics Learning motifs

8
Reinforcement Learning
  • Reinforcement learning can help machines achieve
    feats like figuring out how to play video games
    through trial-and-error, based on working out
    what increases its score.
  • No supervised output but delayed reward
  • Credit assignment problem (what was responsible
    for the outcome)
  • Applications
  • Game playing
  • Robot in a maze
  • Multiple agents, partial observability, ...

9
Examples of Machine Learning Problems
  • Pattern Recognition
  • Facial identities or facial expressions
  • Handwritten or spoken words (e.g., Siri)
  • Medical images
  • Sensor Data/IoT
  • Optimization
  • Many parameters have hidden relationships that
    can be the basis of optimization
  • Pattern Generation
  • Generating images or motion sequences
  • Anomaly Detection
  • Unusual patterns in the telemetry from physical
    and/or virtual plants (e.g., data centers)
  • Unusual sequences of credit card transactions
  • Unusual patterns of sensor data from a nuclear
    power plant
  • or unusual sound in your car engine or
  • Prediction
  • Future stock prices or currency exchange rates

10
THANK YOU!!!!!
  • For More Details Contact Near learn
  • 91-9739305140
  • Email info_at_nearlearn.com
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