The Power to Predict: Predictive Analytics
Prediction
is Power & it’s booming. Predictive modeling offers a clear view of the
present and deeper insight into the future. Predictive analytics uses different
techniques and algorithms from statistics and data mining to analyze current
and historic data to predict the outcome of future events and interactions with
greater accuracy and specificity.
Predictive Analytics reinvents industries and runs the
world. More and more, it drives commerce, manufacturing, healthcare,
government, and law enforcement. Making any predictions poses a tough
challenge. Each prediction depends on multiple factors: The various
characteristics known about each product, every address, each consumer, and
each message. It starts with a business goal: to use data to reduce waste, save
time, or cut costs. How shall we putt all these scattered pieces together for
making each prediction? The idea is simple, this challenge is tackled by a
systematic, scientific means to develop and continually improve prediction—to
literally learn to predict. The solution is Machine
Learning.
Steps involved in Predictive Analytics are:
- Collect Data/Data Collection
- Clean Data/Data Cleaning
- Data Selection & Transformation
- Data Mining
- Identify Patterns/Pattern Evaluation
- Make Predictions
Every business professional in the modern age knows
the importance of data. But these data are scattered heterogeneously. Here
Predictive Analytics with the help of Machine Learning makes it possible to
extract the useful data & manipulate it as per the need and make
predictions based on Company’s requirement. Companies like Google, Amazon or
Netflix are considered innovators in the B2C economy because of their use of
analytics knowledge and application to understand buyer needs and offer
customer requirements.
Machine Learning 2018 Congress has Predictive
Analytics session.
For more details check out the website: https://machinelearning.conferenceseries.com/
Contact: Amelia Smith
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