Towards AI

JULY 19, 2023

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. Data Preparation — Collect data, Understand features 2.

Cross Validation 98

Cross Validation Clustering EDA Data Preparation 98

Dataconomy

AUGUST 16, 2023

” The answer: they craft predictive models that illuminate the future ( Image credit ) Data collection and cleaning : Data scientists kick off their journey by embarking on a digital excavation, unearthing raw data from the digital landscape. Interprets data to uncover actionable insights guiding business decisions.

Data Scientist 172

Data Scientist Data Science Machine Learning Machine Learning 172

Kaggle

JULY 29, 2020

All of the notebooks are in Python. Round 2: Task 1: Population Task 2: Relevant Factors Task 3: Patient Descriptions Task 4: Models and Open Questions Task 5: Materials Task 6: Diagnostics Task 7: Therapeutics Task 8: Risk Factors Full Task CSV Export List There is also a separate Python project on github, cord19q.

ETL 71

ETL Data Scientist Machine Learning Machine Learning 71

Becoming Human

MAY 15, 2023

One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. Python is a High-level, Procedural, and object-oriented language; it is also a vast language itself, and covering the whole of Python is one the worst mistakes we can make in the data science journey.

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

ODSC - Open Data Science

AUGUST 9, 2023

The inferSchema parameter is set to True to infer the data types of the columns, and header is set to True to use the first row as headers. For a comprehensive understanding of the practical applications, including a detailed code walkthrough from data preparation to model deployment, please join us at the ODSC APAC conference 2023.

Machine Learning 52

Machine Learning Machine Learning AWS Big Data 52

The MLOps Blog

MAY 31, 2023

The objective of an ML Platform is to automate repetitive tasks and streamline the processes starting from data preparation to model deployment and monitoring. So, we need to build a verification layer that runs based on a set of rules to verify and validate data before preparing it for model training.

ML 59

ML ML Algorithm Machine Learning 59