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Day 4-Anomaly Detections

Definition: Identification of rare items, events, or observations which is different from currents datasets.



Categories:

1.Point: a single instance of data is abnormal.

2.Contextual: abnormal in the context.

3.Collective Anomaly: a set of data is abnormal.



Applications:

1.Fraud Detection.

2.Event detection in the sensor.

3.Abnormal in sales Drop.



Project: Land Price Prediction using Linear Regression.

Youtube video:https://lnkd.in/eSTvVDE



Day 5-Neural Network

Definition: An algorithm inspired by the structure of the human brain, used for Recognizing the pattern.



It is a set of neurons organized in layers is learning how to classify an input through adjusting it is weights based on the previous example.



Elements:

Neurons, Weights, Activation Functions, and Layers.


Types of Neural Networks:

Perception, Multi-Layer perception, Field Forward Neural Network, Convolution Neural Network, and Radial Basis Functions.


Thanks to Sanjay Kumar A P and Pantech Solutions Pvt Ltd (Pantech ProLabs India) for conduction this free webinar.



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