Can you cut the time a Mercedes-Benz spends on the test bench?

Table of content :

  1. Business Problem
  2. Objective of the Project
  3. Data Description
  4. First Cut Approach
  5. Explore Data Analysis
  6. Existing approach of the problem
  7. Feature Engineering part 1
  8. Feature Engineering part 2
  9. Feature Engineering part 3
  10. Model Selection and Hyper-parameter Tuning
  11. Model comparison
  12. Kaggle Submission
  13. Future Work
  14. Reference

1. Business Problem :

1.1 Introduction :

Since the first automobile, the Benz Patent Motor Car in 1886, Mercedes-Benz has stood for important automotive innovations. These include, for example, the passenger safety cell with crumple zone, the airbag and intelligent assistance systems. Mercedes-Benz applies for nearly 2000 patents…


Recommend blogs to users using content based and collaborating filtering

source

Table of Content :

  1. What is recommendation system
  2. Why recommendation is useful
  3. How recommendation system works
  4. Data Insight
  5. Exploratory Data Analysis
  6. Data preprocess
  7. Collaborating filtering method
  8. Content based filtering method

1. What is Recommendation System :

Once you are new in high-school and everyone stranger for you. When one boy get closer to you and given his introduction and you gives your, but after some conversation you found out he liked rap songs and you like too, after depth conversation related to rap songs, you suggest him some Eminem’s rap songs which he never listen this is called recommendation.

Recommender systems are machine learning systems that help users discover new…


Predict medical report from x-ray image

Table of content :

  1. Introduction
  2. Prerequisite
  3. Business Problem
  4. ML Formulation
  5. Data source and Data overview
  6. Data Preparation
  7. Exploratory Data Analysis
  8. Basic Model [Encoder-Decoder]
  9. Main Model [Encoder-Decoder with Attention]
  10. Error-Analysis
  11. Model-Deployment
  12. Future work
  13. Reference
  14. Profile

1. Introduction :

Tank Mitesh

Learning Machine Learning

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