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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