Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. They build production-ready systems using best-practice containerisation technologies, ETL tools and APIs.

Data Science 130

Data Science Data Scientist ML ML 130

Data Science Dojo

JULY 3, 2024

Statistics : Fundamental statistical concepts and methods, including hypothesis testing, probability, and descriptive statistics. Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Statistical Analysis: Hypothesis testing, probability, regression analysis, etc. ETL Tools: Apache NiFi, Talend, etc. Read more to know. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? Explain the Extract, Transform, Load (ETL) process. The ETL process involves extracting data from source systems, transforming it into a suitable format or structure, and loading it into a data warehouse or target system for analysis and reporting.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

AUGUST 9, 2024

Understanding ETL (Extract, Transform, Load) processes is vital for students. Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics. Students should learn about data wrangling and the importance of data quality.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

The MLOps Blog

MAY 31, 2023

This is the ETL (Extract, Transform, and Load) layer that combines data from multiple sources, cleans noise from the data, organizes raw data, and prepares for model training. are captured and compared by formulating a hypothesis test to conclude with statistical significance.

ML 59

ML ML Algorithm Machine Learning 59