KDnuggets

MARCH 20, 2024

Are you curious about what it takes to become a professional data scientist? By following these guides, you can transform yourself into a skilled data scientist and unlock endless career opportunities. Look no further!

Exploratory Data Analysis 301

Exploratory Data Analysis Data Wrangling Clean Data Data Analysis 301

Data Science Dojo

DECEMBER 14, 2023

The data sets are categorized according to varying difficulty levels to be suitable for everyone. How to tune LLM Parameters for optimal performance Shape your model’s performance using LLM parameters.

Natural Language Processing 195

Natural Language Processing Exploratory Data Analysis Machine Learning Machine Learning 195

Data Science Dojo

DECEMBER 14, 2023

The data sets are categorized according to varying difficulty levels to be suitable for everyone. Link to blog -> Datasets to uplift skills How to tune LLM Parameters for optimal performance Shape your model’s performance using LLM parameters.

Data Science 195

Data Science Natural Language Processing AI AI 195

Dataconomy

MAY 16, 2023

They employ statistical and mathematical techniques to uncover patterns, trends, and relationships within the data. Data scientists possess a deep understanding of statistical modeling, data visualization, and exploratory data analysis to derive actionable insights and drive business decisions.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

JULY 18, 2023

Dealing with large datasets: With the exponential growth of data in various industries, the ability to handle and extract insights from large datasets has become crucial. Data science equips you with the tools and techniques to manage big data, perform exploratory data analysis, and extract meaningful information from complex datasets.

Computer Science 52

Computer Science Computer Science Data Science Machine Learning 52

Pickl AI

FEBRUARY 12, 2024

Data Wrangling and Cleaning Interviewers may present candidates with messy datasets and evaluate their ability to clean, preprocess, and transform data into usable formats for analysis. However, there are a few fundamental principles that remain the same throughout. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JULY 20, 2023

Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA). Extract valuable insights and patterns from the dataset using data visualization libraries like Matplotlib or Seaborn.

Analytics 40

Analytics Analytics Big Data Big Data 40