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The Lifecycle of Feature Engineering: From Raw Data to Model-Ready Inputs

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By Jayita Gulati on July 16, 2025 in Machine Learning Image by Editor In data science and machine learning, raw data is rarely suitable for direct consumption by algorithms. Feature engineering can impact model performance, sometimes even more than the choice of algorithm itself. Data audit : Identify variable types (e.g.,

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How to Work Smarter, Not Harder, with Artificial Intelligence

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Yet, navigating the world of AI can feel overwhelming, with its complex algorithms, vast datasets, and ever-evolving tools. Essential AI Skills Guide TL;DR Key Takeaways : Proficiency in programming languages like Python, R, and Java is essential for AI development, allowing efficient coding and implementation of algorithms.

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Data Scientist Job Description – What Companies Look For in 2025

Pickl AI

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.

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Data Science Dojo - Untitled Article

Data Science Dojo

It could explain how these distributions are used in different machine learning algorithms and why understanding them is crucial for data scientists. 32 datasets to uplift your skills in data science Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.

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Top 7 data science, AI and large language models blogs of 2023

Data Science Dojo

It could explain how these distributions are used in different machine learning algorithms and why understanding them is crucial for data scientists. The data sets are categorized according to varying difficulty levels to be suitable for everyone. This blog will discuss the different natural language processing applications.

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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Since the field covers such a vast array of services, data scientists can find a ton of great opportunities in their field. Data scientists use algorithms for creating data models.

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LLMOps demystified: Why it’s crucial and best practices for 2023

Data Science Dojo

Development to production workflow LLMs Large Language Models (LLMs) represent a novel category of Natural Language Processing (NLP) models that have significantly surpassed previous benchmarks across a wide spectrum of tasks, including open question-answering, summarization, and the execution of nearly arbitrary instructions.