100-days-of-ml-code

100 Days of ML Coding

30-days-of-ml

Kaggle's 30 Days Of Machine Learning Challenge

8-week-sql-challenge

Case study answers for #8WeekSQLChallenge at https://8weeksqlchallenge.com

applying-data-analytics-in-marketing

Exercicios do coursera dataanalitycs com Knitr

bank-marketing-campaign-analysis

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

bianalyst

bigdatac

Data sets and scripts for Coursera Big Data Specialization.

chatgpt-chrome-extension

A ChatGPT Chrome extension. Integrates ChatGPT into every text box on the internet.

daftar-api-lokal-indonesia

Berisi API tentang Data Indonesia ataupun API yang dibuat oleh developer Indonesia <3

data-science-article

Collection of My Data Science article with Code to help you learn and play around.

data-science-for-marketing-analytics

Achieve your marketing goals with the data analytics power of Python

data-science-purwadhika

Data Science Job Connector Master Material

data_visualization

In this hands-on course, you'll learn how to take your data visualizations to the next level with seaborn, a powerful but easy-to-use data visualization tool. To use seaborn, you'll also learn a bit about how to write code in Python, a popular programming language. That said, the course is aimed at those with no prior programming experience, and each chart uses short and simple code, making seaborn much faster and easier to use than many other data visualization tools (such as Excel, for instance).

datasciencecoursera

Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.

datav2-labs

deeplearning.ai-natural-language-processing-specialization

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

digital-marketing-analytics

This contains projects based on Algorithmic Marketing like Marketing Mix Modeling, Attribution Modeling & Budget Optimization, RFM Analysis, Customer Segmentation, Recommendation Systems, and Social Media Analytics

firstproject_machine-learning

this is my first project to study machine learning specifically image classification, natural language processing, time series and image classification with deployment

intro_to_sql

Structured Query Language, or SQL, is the programming language used with databases, and it is an important skill for any data scientist. In this course, you'll build your SQL skills using BigQuery, a web service that lets you apply SQL to huge datasets. In this lesson, you'll learn the basics of accessing and examining BigQuery datasets. After you have a handle on these basics, we'll come back to build your SQL skills.

iykra-data-fellowship

iykra-fellowship-data-science

This is my notebook about data science learn from data science fellowship iykra

kafka-streams-examples

Demo applications and code examples for Apache Kafka's Streams API.

kaggle-data-cleaning-challenge

Learn professional data cleaning techniques! Data cleaning is a key part of data science, but it can be deeply frustrating. Why are some of your text fields garbled? What should you do about those missing values? Why aren’t your dates formatted correctly? How can you quickly clean up inconsistent data entry? In this five day challenge, you'll learn why you've run into these problems and, more importantly, how to fix them! In this challenge we’ll learn how to tackle some of the most common data cleaning problems so you can get to actually analyzing your data faster. We’ll work through five hands-on exercises with real, messy data and answer some of your most commonly-asked data cleaning questions. Here's a day-by-day breakdown of what we'll be learning each day: Day 1: Handling missing values Day 2: Data scaling and normalization Day 3: Cleaning and parsing dates Day 4: Character encoding errors (no more messed up text fields!) Day 5: Fixing inconsistent data entry &amp spelling errors

m-analytics

Coursera course: Marketing Analytics

marketing-analytics-course

marketing-data-science

Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

mathematics-statistics-for-data-science

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

nd0067-c2-creating-an-api-with-postgresql-and-express-project-starter

predict-future-sales

It is from a kaggle competition where we have to predict the future sales using Machine Learning or Deep Learning. It is a Advanced Regression Problem where Statistics and time series analysis is also required. This problem can be very well done by Deep Learning's Model Recurrent Neural Networks.

regitardia