Data Science Dojo

AUGUST 28, 2023

Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production. Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM.

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Pickl AI

JUNE 5, 2025

Key Responsibilities of a Data Scientist in India While the core responsibilities align with global standards, Indian data scientists often face unique challenges and opportunities shaped by the local market: Data Acquisition and Cleaning: Extracting data from diverse sources including legacy systems, cloud platforms, and third-party APIs.

Data Scientist 52

Data Scientist Data Science Power BI Machine Learning 52

Heartbeat

MARCH 21, 2023

In this tutorial, we will go through steps on how to use Comet to monitor our time-series forecasting model. We will carry out some EDA on our dataset, and then we will log the visualizations onto the Comet experimentation website or platform. Comet has another noteworthy feature: it allows us to conduct exploratory data analysis.

Exploratory Data Analysis 59

Exploratory Data Analysis EDA Machine Learning Machine Learning 59

Pickl AI

JULY 25, 2023

Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. They clean and preprocess the data to remove inconsistencies and ensure its quality. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

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Mlearning.ai

JUNE 16, 2023

Generative AI can be used to automate the data modeling process by generating entity-relationship diagrams or other types of data models and assist in UI design process by generating wireframes or high-fidelity mockups. diagram Using ChatGPT to build system diagrams — Part II Generate C4 diagrams using mermaid.js

AI 52

AI AI Data Analysis Data Analysis 52

Iguazio

DECEMBER 14, 2023

There are 6 high-level steps in every MLOps project The 6 steps are: Initial data gathering (for exploration). Exploratory data analysis (EDA) and modeling. Data and model pipeline development (data preparation, training, evaluation, and so on). Deploy according to various strategies.

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ML ML Data Science Data Preparation 52

The MLOps Blog

DECEMBER 28, 2022

Data scientists frame the business problem and the objective into a statistical solution and start with the very first step of data exploration. EDA, as it is popularly called, is the pivotal phase of the project where discoveries are made. Approvals from stakeholders ML projects are inherently iterative by nature.

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ML ML Data Scientist Machine Learning 78