Dataconomy

AUGUST 16, 2023

But make no mistake; data science is not a solitary endeavor; it’s a ballet of complexities and creativity. Data scientists waltz through intricate datasets, twirling with statistical tools and machine learning techniques. Exploring the question, “What does a data scientist do?

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Data Scientist Data Science Machine Learning Machine Learning 172

Towards AI

AUGUST 16, 2023

Gungor Basa Technology of Me There is often confusion between the terms artificial intelligence and machine learning. An agent is learning if it improves its performance based on previous experience. When the agent is a computer, the learning process is called machine learning (ML) [6, p.

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AI AI Machine Learning Machine Learning 98

AWS Machine Learning Blog

SEPTEMBER 12, 2023

The machine learning (ML) model classifies new incoming customer requests as soon as they arrive and redirects them to predefined queues, which allows our dedicated client success agents to focus on the contents of the emails according to their skills and provide appropriate responses. Huy Dang Data Scientist at Scalable GmbH.

Data Science 121

Data Science Data Scientist AWS ML 121

Becoming Human

MAY 15, 2023

For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis. First learn the basics of Feature Engineering, and EDA then take some different-different data sheets (data frames) and apply all the techniques you have learned to date.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence.

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Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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Machine Learning Machine Learning Natural Language Processing Data Preparation 78

Towards AI

JULY 19, 2023

This is part 2, and you will learn how to do sales prediction using Time Series. Please refer to Part 1– to understand what is Sales Prediction/Forecasting, the Basic concepts of Time series modeling, and EDA I’m working on Part 3 where I will be implementing Deep Learning and Part 4 where I will be implementing a supervised ML model.

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Cross Validation Clustering EDA Data Preparation 98

Pickl AI

MAY 30, 2024

You will collect and clean data from multiple sources, ensuring it is suitable for analysis. You will perform Exploratory Data Analysis to uncover patterns and insights hidden within the data. Also Read: Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

AWS Machine Learning Blog

MAY 30, 2023

Since its introduction, we have helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. In this series of posts, we share lessons learned about optimizing costs in Amazon SageMaker. For example, ml.t2.medium

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AWS ML ML EDA 93

Pickl AI

FEBRUARY 4, 2025

Example Use Cases Matplotlib is ideal for Data Analysis , scientific research, and Machine Learning projects. Researchers and analysts commonly use it to explore data distributions, plot trends, and present findings. Aesthetic Mapping: Utilises color, size, and shape to represent data variables.

Python 52

Python Exploratory Data Analysis Data Analysis Data Analysis 52

Iguazio

DECEMBER 14, 2023

Who This Book Is For This book is for practitioners in charge of building, managing, maintaining, and operationalizing the ML process end to end: Data science / AI / ML leaders: Heads of Data Science, VPs of Advanced Analytics, AI Lead etc. Exploratory data analysis (EDA) and modeling.

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ML ML Data Science Data Preparation 52

The MLOps Blog

MAY 31, 2023

Getting machine learning to solve some of the hardest problems in an organization is great. In this article, I will share my learnings of how successful ML platforms work in an eCommerce and what are the best practices a Team needs to follow during the course of building it. How to set up an ML Platform in eCommerce?

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ML ML Algorithm Machine Learning 59

Kaggle

JULY 29, 2020

With sports (and everything else) cancelled, this data scientist decided to take on COVID-19 | A Winner’s Interview with David Mezzetti When his hobbies went on hiatus, Kaggler David Mezzetti made fighting COVID-19 his mission. Photo by Clay Banks on Unsplash Let’s learn about David! How did you spend your time on this competition?

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ETL Data Scientist Data Science Machine Learning 71