by A Selcia

1. MACHINE LEARNING
ALGORITHMS IN BIG DATA
PREPARED BY
M.Priyadharshini
A.Selcia
II Year CSE

2. Machine learning is a
important component of
artificial intelligence.
Machine learning is collection.
of data and prediction data for
industrial applications
Data analytics is required
staticstics,artificial intelligence,
data mining,deep learning. .
WHAT IS MACHINE
LEARNING?

3. Supervised learning Map from input to an output
Unsupervised learning Input data and no corresponding output
Reinforcement learning To design a mathematical framework to
solve the program
CLASSIFICATION OF MACHINE LEARNING

4. Image recognition Speech recognition
Traffic recognition Product Recommendation
Self driving cars filter Email-spam malware
Virtual personal assistant Online fraud detection
Stock marketing Medical dignosis
Automatic language
translation

5. There are different applications of machine learning
technologies including of diagnostics, forecasting, customer
segmentation, big data visualization, robot navigation, process
optimization, real-time decisions, meaningful compression,
fraud detections, games, finance for option pricing, remote
sensing, business management, engineering, energy,
consumption, healthcare, agriculture, and fault diagnosis, etc…
In the finance sector, it is suitable to find fraud detections,
and focused on the account holder, whereas in the retail sector, it
is suitable to find product recommendations and improvement of
customer services

6. Importance of data science and engineering

7. • Machine learning algorithm becomes crucial when a large
number of datasets exist in healthcare sector.
Machine learning (ML) is keeping busy healthcare-related
researchers to provide meaningful results with clinically
reliable predictions.
Machine learning in Alzheimer’s diseases and mild
cognitive impairment diagnosis
MACHINE LEARNING
ALGORITHM IN HEALTHCARE
SECTORS

8. Machine learning in healthcare sector

10. MACHINE LEARNING IN HEALTHCARE
Predicts illnesses and treatments
Forecasts health risks to various populations of people
Assists with healthcare records and workflow
Differentiates between tumors and healthy anatomy
Aids in drug development, lowering costs
Identifies opportunities for clinical trials
Detects gaps in healthcare
Assists pathologists to make faster and more accurate diagnosis

11. The machine learning concept applicable to
various applications. So far various works have
been done in big data-based applications but still,
various challenges need to address differently.
The different related work of machine learning in
big data applications especially in the case of the
healthcare sector and production and material
segment.
CONCLUSION

12. THANK YOU