Analytics Vidhya

APRIL 28, 2023

Introduction If you work with programming languages and are familiar with Python, you must have had a brush with Pandas, a robust yet flexible data manipulation and analysis library. It was founded by Wes McKinney in 2008. appeared first on Analytics Vidhya.

Data Analysis 328

Data Analysis Data Analysis Python Analytics 328

Dataconomy

JANUARY 13, 2017

You could dive into gigabytes or even petabytes of data from any industry and derive meaningful interpretations that may catch even the industry insiders by surprise. When the global financial crisis hit the American market in 2008, few.

Big Data 195

Big Data Big Data Data Analysis Data Analysis 195

Analytics Vidhya

JULY 17, 2024

Introduction If you’ve been in the data field for quite some time, you’ve probably noticed that some technical skills are becoming more dominant, and the data backs this up. Until the release of NumPy in 2005, Python was considered slow for numeric analysis. But Numpy changed that.

Python 285

Python Analytics Analytics Data Analysis 285

Mlearning.ai

APRIL 25, 2023

Photo by Juraj Gabriel on Unsplash Data analysis is a powerful tool that helps businesses make informed decisions. In this blog, we’ll be using Python to perform exploratory data analysis (EDA) on a Netflix dataset that we’ve found on Kaggle. df['rating'].replace(np.nan, value_counts()[:20].plot(kind="bar",color="Blue")

Data Analysis 52

Data Analysis Data Analysis Python Exploratory Data Analysis 52

Towards AI

AUGUST 25, 2023

MIT Overview of AI and ML Source: Toward Data Science Project Definition The first step in AI projects is to define the problem. LeGro, “ Interpreting Confusing Multiple Linear Regression Results,” Towards Data Science, Sep. McKinney, Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, 2nd ed.,

Machine Learning 98

Machine Learning Machine Learning AI AI 98

O'Reilly Media

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hadoop 137

Hadoop Algorithm ML ML 137

Dataconomy

MARCH 5, 2025

As the demand for data expertise continues to grow, understanding the multifaceted role of a data scientist becomes increasingly relevant. What is a data scientist? A data scientist integrates data science techniques with analytical rigor to derive insights that drive action.

Data Scientist 91

Data Scientist Citizen Data Scientist Exploratory Data Analysis Machine Learning 91