Mlearning.ai

MAY 23, 2023

Blind 75 LeetCode Questions - LeetCode Discuss Data Manipulation and Analysis Proficiency in working with data is crucial. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Mlearning.ai

JULY 11, 2023

For example, when it comes to deploying projects on cloud platforms, different companies may utilize different providers like AWS, GCP, or Azure. Therefore, having proficiency in a specific cloud platform, such as Azure, does not mean you will exclusively work with that platform in the industry.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40

Mlearning.ai

JUNE 16, 2023

How to use the Codex models to work with code - Azure OpenAI Service Codex is the model powering Github Copilot. GPT-4 Data Pipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API. The data would be interesting to analyze. The article has good points with any LLM Use prompt to guide.

AI 52

AI AI Data Analysis Data Analysis 52

Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. Exploratory Data Analysis (EDA) EDA is a crucial preliminary step in understanding the characteristics of the dataset.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

The MLOps Blog

MAY 31, 2023

There can be multiple sources of data at the same time, which can be available in different forms like image, text, and tabular form. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data. How to set up a data processing platform?

ML 59

ML ML Algorithm Machine Learning 59

Heartbeat

MAY 29, 2023

It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model. It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

Towards AI

JANUARY 22, 2025

The role of a data scientist is changing so fast that often schools cant keep up. Universities still mostly focus on things like EDA, data cleaning, and building/fine-tune models. Simply put, focusing solely on data analysis, coding or modeling will no longer cuts it for most corporate jobs. What to do then?

Data Scientist 105

Data Scientist EDA Exploratory Data Analysis AI 105