ODSC - Open Data Science

DECEMBER 7, 2023

ML Pros Deep-Dive into Machine Learning Techniques and MLOps Seth Juarez | Principal Program Manager, AI Platform | Microsoft Learn how new, innovative features in Azure machine learning can help you collaborate and streamline the management of thousands of models across teams.

Data Science 98

Data Science Data Wrangling Machine Learning Machine Learning 98

Data Science Dojo

JULY 3, 2024

Statistics : Fundamental statistical concepts and methods, including hypothesis testing, probability, and descriptive statistics. Cloud Computing : Utilizing cloud services for data storage and processing, often covering platforms such as AWS, Azure, and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. Scalability Considerations Scalability is a key concern in model deployment.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Becoming Human

MAY 15, 2023

In Inferential Statistics, you can learn P-Value , T-Value , Hypothesis Testing , and A/B Testing , which will help you to understand your data in the form of mathematics. Three of the most popular cloud platforms are Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

JULY 25, 2023

Statistical Analysis: Hypothesis testing, probability, regression analysis, etc. Cloud Platforms: AWS, Azure, Google Cloud, etc. Skills and Tools of Data Scientists To excel in the field of Data Science, professionals need a diverse skill set, including: Programming Languages: Python, R, SQL, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 27, 2024

Statistical Analysis and Testing R’s rich ecosystem for hypothesis testing, regression modelling, and Bayesian analysis makes it ideal for statistical tasks. These containers ensure consistency and simplify deploying workflows in cloud services like AWS , Google Cloud, or Azure.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

The MLOps Blog

MAY 31, 2023

To store Image data, Cloud storage like Amazon S3 and GCP buckets, Azure Blob Storage are some of the best options, whereas one might want to utilize Hadoop + Hive or BigQuery to store clickstream and other forms of text and tabular data. are captured and compared by formulating a hypothesis test to conclude with statistical significance.

ML 59

ML ML Algorithm Machine Learning 59