Pickl AI

DECEMBER 3, 2024

With the explosion of data in recent years, it has become essential for data scientists and Machine Learning practitioners to understand and effectively apply preprocessing techniques. Loading the dataset allows you to begin exploring and manipulating the data. During EDA, you can: Check for missing values.

Python 52

Python ML ML Exploratory Data Analysis 52

Pickl AI

MAY 30, 2024

It’s crucial to grasp these concepts, considering the exponential growth of the global Data Science Platform Market, which is expected to reach 26,905.36 Similarly, the Data and Analytics market is set to grow at a CAGR of 12.85% , reaching 15,313.99 billion INR by 2027. billion INR by 2026, with a CAGR of 27.7%.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

JANUARY 3, 2024

Skill Demand: Machine Learning skills are in high demand globally, contributing to a 23% expected churn in the job market by 2027. Our aim is to build a robust foundation in core Machine Learning concepts and offer hands-on experience in Exploratory Data Analysis and Feature Engineering. between 2023 and 2030.

Machine Learning 52

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Mlearning.ai

APRIL 25, 2023

In this blog, we’ll be using Python to perform exploratory data analysis (EDA) on a Netflix dataset that we’ve found on Kaggle. We’ll be using various Python libraries, including Pandas, Matplotlib, Seaborn, and Plotly, to visualize and analyze the data. df = df.dropna() df.isnull().sum() sum() df['rating'].value_counts()

Data Analysis 52

Data Analysis Data Analysis Python Exploratory Data Analysis 52