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From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams

Towards AI

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

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Predicting new and existing product sales in semiconductors using Amazon Forecast

AWS Machine Learning Blog

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. We evaluated the WAPE for all BLs in the auto end market for 2019, 2020, and 2021.

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Unveiling Market Dynamics: Winners of the Google Trends Analysis and Predictive Modeling

Ocean Protocol

Podium Introduction Participants in the “Google Trends” Data Challenge analyzed the influence of public search interest on cryptocurrency market prices. The challenge required a detailed analysis of Google Trends data, integration of additional data sources, and the application of advanced ML methods to predict market behaviors.

EDA 59
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Sailing into 2024: Machine Learning salary trends unveiled

Pickl AI

Google, a tech powerhouse, offers insights into the upper echelons of ML salaries in the United States. In 2024, the significance of Machine Learning (ML) cannot be overstated. The global ML market is projected to soar from $26.03 It is vital to understand the salaries of Machine learning experts in India.

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Linear Regression for tech start-up company Cars4U in Python

Mlearning.ai

In 2018–2019, while new car sales were recorded at 3.6 As a data scientist at Cars4U, I had to come up with a pricing model that can effectively predict the price of used cars and can help the business in devising profitable strategies using differential pricing. million units, around 4 million second-hand cars were bought and sold.

Python 52
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Text to Exam Generator (NLP) Using Machine Learning

Mlearning.ai

Exploratory Data Analysis This is one of the fun parts because we get to look into and analyze what’s inside the data that we have collected and cleaned. I also learned and absorbed a lot of things related to AI and more precisely machine learning (ML) including how to train the model, and terms related to that.

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Meet the winners of the Unsupervised Wisdom Challenge!

DrivenData Labs

Summary of approach : Using a downsampling method with ChatGPT and ML techniques, we obtained a full NEISS dataset across all accidents and age groups from 2013-2022 with six new variables: fall/not fall, prior activity, cause, body position, home location, and facility. Check out zysymu's full write-up and solution in the competition repo.