navinmundhra Goto Github PK

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Name: Navin Mundhra

Type: User

Bio: Data science & Machine Learning enthusiast | Coder | Speaker | Videographer

Location: Kolkata, India

Navin Mundhra's Projects

01_loan_status_classification

Problem Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customers segments, those are eligible for loan amount so that they can specifically target these customers. Here they have provided a partial data set.

02_dl_num_reader

A basic number identification model.

03_big_mart_sales_prediction

The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet. Using this model, BigMart will try to understand the properties of products and outlets which play a key role in increasing sales.

04_mobility_analytics

With the upcoming cab aggregators and demand for mobility solutions, the past decade has seen immense growth in data collected from commercial vehicles with major contributors such as Uber, Lyft and Ola to name a few. There are loads of innovative data science and machine learning solutions being implemented using such data and that has led to tremendous business value for such organizations.

05_ml_for_banking

The process, defined as ‘risk-based pricing’, uses a sophisticated algorithm that leverages different determining factors of a loan applicant. Selection of significant factors will help develop a prediction algorithm which can estimate loan interest rates based on clients’ information. On one hand, knowing the factors will help consumers and borrowers to increase their credit worthiness and place themselves in a better position to negotiate for getting a lower interest rate. On the other hand, this will help lending companies to get an immediate fixed interest rate estimation based on clients information. Here, your goal is to use a training dataset to predict the loan rate category (1 / 2 / 3) that will be assigned to each loan in the test set.

06_employee_attrition_rate

Employees are the most important part of an organization. Successful employees meet deadlines, make sales, and build the brand through positive customer interactions. Employee attrition is a major cost to an organization and predicting such attritions is the most important requirement of the Human Resources department in many organizations. In this problem, your task is to predict the attrition rate of employees of an organization.

07_video_game_sales

The gaming industry is certainly one of the thriving industries of the modern age and one of those that are most influenced by the advancement in technology. With the availability of technologies like AR/VR in consumer products like gaming consoles and even smartphones, the gaming sector shows great potential. In this hackathon, you as a data scientist must use your analytical skills to predict the sales of video games depending on given factors. Given are 8 distinguishing factors that can influence the sales of a video game. Your objective as a data scientist is to build a machine learning model that can accurately predict the sales in millions of units for a given game.

08_birdcall_identification

While audio compression has been the most prominent application of digital audio processing, the gathering importance of data abundance is seeing growing applications of signal processing in audio segmentation and classification. Audio classification is a part of the larger problem of audiovisual data handling. Audio classification is also useful as a front end to audio compression systems where the efficiency of coding and transmission is facilitated by matching the compression method to the audio type, as for example, speech or music. That is exactly what the problem description is in this competition! Identification of a wide variety of bird vocalizations in soundscape recordings which might have anthropogenic sounds (e.g., airplane overflights) or other bird and non-bird (e.g., chipmunk) calls in the background, with a particular labeled bird species in the foreground.

navinmundhra Goto Github PK

Navin Mundhra's Projects

01_loan_status_classification

02_dl_num_reader

03_big_mart_sales_prediction

04_mobility_analytics

05_ml_for_banking

06_employee_attrition_rate

07_video_game_sales

08_birdcall_identification

my_research

navinmundhra.github.io

wikipedia_data_stream_handling

xx_data_extraction_scripts

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