Ramgopal Prajapat:

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Cox Regression - Survival Modeling Ram - Dec 19, 2020
In this blog, the focus is on Cox Proportional Hazards (PH) model. The Cox Proportional hazard model is also referred to by the Cox Model, Cox Regression, or Proportional Hazard Model. Cox Model is used for the analysis of Survival data and finding out the relationship between Survival Time and …
CHAID Decision Tree: Reverse Mortgage Loan Termination Example Ram - Dec 16, 2020
Reverse Mortgage Loan (RML) enables Senior Citizens to avail of periodical payments from a lender against the mortgage of his/her house to supplement their income while remaining the owner and occupying the house. Interest on the payments availed will be accumulated. One of the types of A reverse mortgage is …
Customer Life Cycle and Customer Retention Management Ram - Dec 11, 2020
The Customer Life Cycle typically has 3 phases –Acquisition, Growth, and Retention. Customer Acquisition: Focus is targeting & reaching out to prospects, explaining to them about the products and services, and on-boarding the customers. Customer Development/Build/Growth: In this phase, organizations leverage the existing relationship for growing the engagement with newly …
Facial Emotion Recognition using Deep Learning Ram - Nov 25, 2020
Found facial expressions of emotion are not culturally determined, but universal across human cultures and thus biological in origin. The 6 basic human emotions are anger, disgust, fear, joy, sadness, and surprise. Reference Source. In this blog, we aim to build a deep learning-based human facial emotion classifier. For building …
Emotion Detection from Text Ram - Nov 23, 2020
Emotion is a complex state of feeling that influences physical and psychological changes. Emotions can be expressed verbally (through words, emojis, or speech - tone of voice) or by using nonverbal expressions such as facial expressions. There are different models to define the type of emotions. 6 basic type of …
Optimization using Python: Linear Programming with example Ram - Nov 09, 2020
In the scenario, there are 64 different foods and their various nutrient contents and calories. Also, the price of each of these food items. We can want to formulate this as a diet optimization problem and find the optimal size of the food intake. A typical optimization scenario will have …
Precision vs Recall in Binary Classification Ram - Nov 06, 2020
In Machine Learning Classification Scenario (especially Binary Classification) various model performance measures are used. In this, we are discussing Precision and Recall with relevant scenarios and examples. In which scenario Precision is more important than Recall and vice versa?
Missing value treatment for Categorical and Numeric Variables using Python Ram - Nov 06, 2020
Missing values are common in real-life scenarios. All of the data science and analytics professionals need to understand strategies to manage missing values. In this blog, we will discuss missing value identification, treatment, and imputation. After reading the blog you will be able to answer these questions. How to identify …