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120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

ad-papers

Papers on Computational Advertising

adf

ai-product-manager-nd

api-pm-training

Training materials to deliver an API Product Owner training. The training follows a "learning by doing" methodology with big emphasis on students solving a realistic problem for the first time with the facilitation of an instructor. The training is split in modules with each module touching upon different areas of responsibilities for an API product owner.

awesome-courses

:books: List of awesome university courses for learning Computer Science!

awesome-product-management

A list of product management resources, curated from 10 years of bookmarks.

awesome-product-management-1

A curated list of awesome resources for product/program managers to learn and grow.

azure-datafactory

azure-synapse-analytics-day

bank-marketing-campaign-analysis

Improve marketing campaign of a Portuguese bank by analyzing their past marketing campaign data and recommending which customer to target

berkeleyx-cs100.1x-big-data-with-apache-spark

This repository contains code files specifically IPython notebooks for the assignments in the course "Introduction to Big Data with Apache Spark" by UC Berkeley and Databricks on edX

beyond-leetcode-sql

Analysis of SQL Leetcode and classic interview questions. Common pitfalls, anti-patterns and handy tricks are discussed. Sample databases are provided.

big-data-mapreduce-course

Big Data Modeling, MapReduce, Spark, PySpark @ Santa Clara University

bus256

Marketing Analytics

cd4ml-scenarios

Repository with sample code and instructions for "Continuous Intelligence" and "Continuous Delivery for Machine Learning: CD4ML" workshops

cerner-machine-learning

ceu_product-analytics

chd

cookbook

The Data Engineering Cookbook

cortana-intelligence-price-analytics

Price analytics solution based on the double-machine-learning modeling approach

customer-analytics-in-python

I use various Data Science and machine learning techniques to analyze customer data using STP framework. I preprocessed the data, performed segmentation, hierarchical clustering, k-means, PCA techniques with a lot of visualizations to segment and understand customer data. I have performed Purchase Analytics (both descriptive analysis and predictive analysis). Used deep learning to enhance my model.

data-engineer-roadmap

Learning from multiple companies in Silicon Valley. Netflix, Facebook, Google, Startups

data-engineering-gcp

Data Engineering on Google Cloud Platform

data-science-algorithms-in-a-week-second-edition

Data Science Algorithms in a Week, Second Edition, published by Packt

data-science-complete-tutorial

Notebooks to learn data science - Videos https://www.edyoda.com/course/1416

data-science-for-marketing-analytics

Achieve your marketing goals with the data analytics power of Python

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data-science-masters

Self-study plan to achieve mastery in data science

data-science-projects-with-python

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn