AI Artificial Intelligence with Python

AI Artificial Intelligence with Python

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What you’ll learn:
  • Our course ensures that you will be able to think with a predictive mindset and understand well the basics of the techniques used in prediction.
  • Critical thinking is very important to validate models and interpret the results. Hence, our course material emphasizes on hardwiring this similar kind
  • You will have good knowledge about the predictive modeling in python, linear regression, logistic regression
  • Learn the fitting model with a sci-kit learn library, the fitting model with stat model library, ROC curves, backward elimination approach,
Description:

It is the use of data and statistics to predict the outcome of the data models. This prediction finds its utility in almost all areas from sports, to TV ratings, corporate earnings, and technological advances. Predictive modeling is also called predictive analytics. With the help of predictive analytics, we can connect data to effective action about the current conditions and future events. Also, we can enable the business to exploit patterns and which are found in historical data to identify potential risks and opportunities before they occur.

Python is used for predictive modeling because Python-based frameworks give us results faster and also help in the planning of the next steps based on the results.

Our course at EDUCBA is tailor-made for people who are willing to work with a framework that delivers the best result in comparison to the rest of the competitive tools in the market.

Our course ensures that you will be able to think with a predictive mindset and understand well the basics of the techniques used in prediction. Critical thinking is very important to validate models and interpret the results. Hence, our course material emphasizes on hardwiring this similar kind of thinking ability.

You will have good knowledge about the predictive modeling in python, linear regression, logistic regression, the fitting model with a sci-kit learn library, the fitting model with stat model library, ROC curves, backward elimination approach, stats model package, etc.

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Who this course is for:
  • This Predictive Modeling with Python Course can be taken up by anyone who shares a decent amount of interest in this field. The earlier someone starts the further they can reach. In the case of students who are pursuing a course in statistics, or computer science graduates it is a very good opportunity to direct your career in that direction. As this is a much demand skill every IT professional is looking for a good switch and entering the domain of predictive analysis. After successfully having hands-on with Predictive Analysis you get open up career opportunities within job roles like that of a Data Analyst, Data Scientist, Business Analyst, Market Research Analyst, Quality Engineer, Solution Architect, Programmer Analyst, Statistical Analyst, Statistician, etc.

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