Data Science Dojo

AUGUST 28, 2023

The scope of LLMOps within machine learning projects can vary widely, tailored to the specific needs of each project. Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production. This includes tokenizing the data, removing stop words, and normalizing the text.

Exploratory Data Analysis 195

Exploratory Data Analysis Data Preparation Machine Learning Machine Learning 195

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.

Cross Validation 98

Cross Validation Clustering EDA Data Preparation 98

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. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

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

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.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

AWS Machine Learning Blog

MAY 30, 2023

For ML model development, the size of a SageMaker notebook instance depends on the amount of data you need to load in-memory for meaningful exploratory data analyses (EDA) and the amount of computation required. As with SageMaker notebooks, you can also feed AWS CUR data into QuickSight for reporting or visualization purposes.

AWS 92

AWS ML ML EDA 92

AWS Machine Learning Blog

SEPTEMBER 12, 2023

Email classification project diagram The workflow consists of the following components: Model experimentation – Data scientists use Amazon SageMaker Studio to carry out the first steps in the data science lifecycle: exploratory data analysis (EDA), data cleaning and preparation, and building prototype models.

Data Science 119

Data Science Data Scientist AWS ML 119