Name: Moin_Dalvs
Type: User
Bio: Data scientist in the making, enthusiast, self-learner, seeking to leverage the machine learning, artificial intelligence, and data science skills
Twitter: DalvsHubot
Location: Navi Mumbai
Moin_Dalvs's Projects
What is Actuarial analyst ? what are their responsibilities, skills required and interview questions
Assignment Basic Stats
Assignment 2 Set 2
Topics: Normal distribution, Functions of Random Variables
Content This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas.This is a systematic approach for identifying and analyzing patterns and trends in crime using USArrest dataset.
Problem Statement Perform clustering (Hierarchical,K means clustering and DBSCAN) for the airlines data to obtain optimum number of clusters
A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and measured? Analyze the data and draw inferences at 5% significance level. Please state the assumptions and tests that you carried out to check validity of the assumptions.
Problem Statement Implement a KNN model to classify the different types of Glass
Problem Statement Implement a KNN model to classify the animals into categories
Predicting Customer Response to Telemarketing Campaigns for Term Deposit
Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model.
Consider only the below columns and prepare a prediction model for predicting Price. Corolla<-Corolla[c("Price","Age_08_04","KM","HP","cc","Doors","Gears","Quarterly_Tax","Weight")]
Problem Statement Prepare a classification model using Naive Bayes for salary data
Case Summary Perform Principal component analysis and perform clustering using first 3 principal component scores (both Heirarchical and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it has 3 clusters)
Use Random Forest to prepare a model on fraud data treating those who have taxable income <= 30000 as "Risky" and others are "Good"
A cloth manufacturing company is interested to know about the segment or attributes causes high sale. Approach - A Random Forest can be built with target variable Sale (we will first convert it in categorical variable) & all other variable will be independent in the analysis.
Extract reviews of any product from ecommerce website like amazon
Build a Book Recommendation System
Hierarchical, KMeans and DBSCAN clustering techniques
P-140 Air Quality forecasting(CO2 emissions) Business Objective: To forecast Co2 levels for an organization so that the organization can follow government norms with respect to Co2 emission levels. Data Set Details: Time parameter and levels of Co2 emission
Course Files for Complete Python 3 Bootcamp Course on Udemy