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azure-data-fundamentals-certification-dp900

For this exam, you should have familiarity with Exam DP-900 - Azure Data Fundamentals

bokeh-python-visualization

A Bokeh project developed for learning and teaching Bokeh interactive plotting!

credit-analysis-study-case

Study case asked by a fintech during interview stage

credit-card-fraud-project-1

### Data Set Information: This dataset is taken from a research explained here. The goal of the research is to help the auditors by building a classification model that can predict the fraudulent firm on the basis the present and historical risk factors. The information about the sectors and the counts of firms are listed respectively as Irrigation (114), Public Health (77), Buildings and Roads (82), Forest (70), Corporate (47), Animal Husbandry (95), Communication (1), Electrical (4), Land (5), Science and Technology (3), Tourism (1), Fisheries (41), Industries (37), Agriculture (200). There are two csv files to present data. Please merge these two datasets into one dataframe. All the steps should be done in Python. Please don't make any changes in csv files. Consider ``Audit_Risk`` as target columns for regression tasks, and ``Risk`` as the target column for classification tasks. ### Attribute Information: Many risk factors are examined from various areas like past records of audit office, audit-paras, environmental conditions reports, firm reputation summary, on-going issues report, profit-value records, loss-value records, follow-up reports etc. After in-depth interview with the auditors, important risk factors are evaluated and their probability of existence is calculated from the present and past records. ### Relevant Papers: Hooda, Nishtha, Seema Bawa, and Prashant Singh Rana. 'Fraudulent Firm Classification: A Case Study of an External Audit.' Applied Artificial Intelligence 32.1 (2018): 48-64.

data-analysis-in-python-with-pandas

This repo has jupyter notebooks for data analysis in python using pandas library. The exercises that I've worked on here are based on video series of Kevin Markham from Data School.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

ecommerce-recommender

Recommendation of E-commerce products & Sentimental analysis of Customer Reviews Using NLP

exploringdatawithpython

Methods of data exploration and visualization using Python.

machine-learning-with-python

Python code for common Machine Learning Algorithms

marketing-mix-modeling

It helps to understand how much each marketing & retail inputs are contributing to sales and performance

mine

all ccodes

nlp-python-deep-learning

NLP in Python with Deep Learning

nlp-with-python

Scikit-Learn, NLTK, Spacy, Gensim, Textblob and more

pet_insurance

NLP analysis and classification of a dataset of claims

portofolio

this repo contains projects related to medical insurance ,data analysis ,feature engineering, NLP ,Fraud detection........

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

ql-case-study

Materials for case study for interview with Quicken Loans

retail-customer-segmentation

Customer Segmentation for an online retail store based on Recency - Frequency - Monetary value (RFM) model, using unsupervised K-means clustering

retail_db

scikit-learn

scikit-learn: machine learning in Python

scrapy_udemy_course

sentimental-analysis-on-customers-opinion

tensorflow_cookbook

Code for Tensorflow Machine Learning Cookbook