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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. Exploratory Data Analysis. Exploratory data analysis is analyzing and understanding data. Deep Learning. Use cases of data science. Ensembling.

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Your Complete Roadmap to Become an Azure Data Scientist

Pickl AI

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. What is Azure?

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Machine Learning Operations (MLOPs) with Azure Machine Learning

ODSC - Open Data Science

This resulted in a wide number of accelerators, code repositories, or even full-fledged products that were built using or on top of Azure Machine Learning (Azure ML). Based on our analysis of these accelerators, we identified design patterns and code that we could leverage. These can include but may not be limited to: a.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

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Nurturing a Strong Data Science Foundation for Beginners

Mlearning.ai

Before diving into the world of data science, it is essential to familiarize yourself with certain key aspects. The process or lifecycle of machine learning and deep learning tends to follow a similar pattern in most companies. Another crucial aspect to consider is MLOps (Machine Learning Operations) activities.

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

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How to Integrate Both Python & R into Data Science Workflows

Pickl AI

Libraries like Pandas and NumPy offer robust tools for data cleaning, transformation, and numerical computing. Scikit-learn and TensorFlow dominate the Machine Learning landscape, providing easy-to-implement models for everything from simple regressions to deep learning.