Credit Default Prediction using Logistic Regression

[mitsumi]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 19 lectures (2h 47m) | Size: 804 MB

Learn the concepts and application of Predictive Modeling tools and visualize data using them

What you'll learn:
Learn mathematical and Physics formulas which are used to define many scientific events such as Linear Regression
Get to know more about data mining, text analytics, and predictive modeling, learn more about terms such as Risk assessment and Fraud detection

Requirements
You should be self-driven and always motivated to learn. Participation in this Predictive Analytics Training requires consistently meeting deadlines
Individuals should be familiar with programming languages such as Python and R as well as coding experience in these languages will be quite helpful in the course.
He/She should have a strong grasp of inferential and descriptive statistics.
He/She should have a strong understanding of the basic programming concepts such as variables, conditions, loops, functions, and some basic data structures such as arrays, objects, lists, etc.

Description
This Video tutorial starts the introduction to the project explaining all its goals and perspective. Further, we'll discuss the Project Steps and files needed to be imported. Next, we'll learn about Data Processing EDA along with concepts such as the Splitting Data and Confusion Matrix. In Continuation, we'll go through the topic Hyper Parameter Tuning and end the video with the concept of Decision Tree, its theory, and code explanation.

Along with the Predictive Analytics Training, we'll get used to many new skills and techniques which help in improving your knowledge base and add weight to your CV. Going along the course you will get to taste many of the mathematical and Physics formulas which are used to define many scientific events such as Linear Regression, etc. Further, we'll get to know more about data mining, text analytics, and predictive modeling, learn more about terms such as Risk assessment and Fraud detection, and also we'll get to know the data cycle defined in stages as data preprocessing, data preparation, model evaluation, and deployment. Programming skills, as well as Analytic skills, are also attained while going through the curriculum of the course. Hence, this Predictive Analytics Course gives you full exposure to the world of predictive analytics and help you step into its world.

Who this course is for
Who has an interest in data and needs to learn to use this data for predictive analysis for predicting future outcomes can go for this Course
Data Analytics, Statistician, or an IT professional looking for a switch in his career in the field of Data Analysis and Predictive Modelling. A research scientist presupposed in Data Analysis, IT specialists, professors, and teachers can opt for this Predictive Analysis Course.

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