₹800
per month
Video
Sep 2018
3hrs 3mins
1st Edition
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• Make your data earn its keep by developing efficient models to predict future results accurately
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• Master the data science forces that drive your company and make the most of these forthcoming opportunities
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• Apply statistical predictive modeling to help your organization make better business decisions
Predicting future trends can be the difference between profit and loss for competitive enterprises. Most businesses state that poor data quality leads to bad decision-making. Further, the predictive analytics market is expected to grow by 22% by 2020. As this technology hits the mainstream, now is the time to consider which predictive modeling techniques will produce the best results for your organization.
Hands-On Statistical Predictive Modeling gives you everything you need to bring the power of statistical predictive models into your statistical or data mining work. However, without the right predictive modeling techniques, analytics projects are unlikely to provide actionable insights. This course will show you how these core algorithms underpin the accuracy and relevance of statistical results and drive competitive differentiation. You will be able to anticipate customer behavior, take steps to cultivate customer loyalty, and capture a greater share of the market. You will be aware of the data science forces shaping your future economy and will have mastered how best to use and seize these coming opportunities.
By the end of this course, you will be able to elevate your company's analytics know-how to enhance its decision-making skills, cost efficiency, and profitability. You will also be able to put these skills to use in your upcoming statistical and data mining projects.
All data files for this course are available on GitHub at https://github.com/PacktPublishing/Hands-On-Statistical-Predictive-Modeling
If you are a statistical or data mining professional and want to add statistical predictive modeling to your skill set, then this is the ideal course for you. Basic statistics knowledge will be helpful, but no prior knowledge of statistical predictive modeling is assumed.
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• Differentiate between various types of predictive models
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• Master linear regression
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• Explore the results of logistic regression
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• Understand when to use discriminant analysis
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• Understand the inner workings of your models
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• Maximize your productivity by analyzing your models and interpreting their accuracy in a well-organized manner