Pickl AI

JULY 25, 2023

Cloud Platforms: AWS, Azure, Google Cloud, etc. in fields like Computer Science, Statistics, or related disciplines. On the other hand, Data Engineers often have a background in Computer Science, Software Engineering, or a related field, but a Bachelor’s degree may suffice in some cases.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Data Science 101

AUGUST 30, 2023

Career advice was not especially good at that time (or I didn’t know what questions to ask) so I had no idea what jobs or careers were out there, but I knew that computers were interesting to me. At the time computer science was presented as a very theoretical degree so I plumped for electronics which seemed more practical.

Computer Science 111

Computer Science Computer Science Azure AWS 111

Pickl AI

MAY 17, 2023

Learning the use of cloud platforms like AWS, Microsoft Azure and Google Cloud can benefit your career as a Data Scientist. Get Experience, Practice and Meet Fellow Data Scientists With hands-on experience in using different tools of Data Science and applying your skills requires immense practice through projects and assignments.

Data Scientist 52

Data Scientist Data Science Data Wrangling SQL 52

Dataconomy

MARCH 13, 2023

Here are some of the essential tools and platforms that you need to consider: Cloud platforms Cloud platforms such as AWS , Google Cloud , and Microsoft Azure provide a range of services and tools that make it easier to develop, deploy, and manage AI applications.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

PyImageSearch

OCTOBER 16, 2023

AWS , GCP , Azure , DigitalOcean , etc.) Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science? You can use Docker to create, handle, manipulate, and run containers on your system locally. That’s not the case.

Deep Learning 128

Deep Learning Deep Learning Machine Learning Machine Learning 128

O'Reilly Media

OCTOBER 19, 2021

Cloud-based data warehouses, such as Snowflake , AWS’ portfolio of databases like RDS, Redshift or Aurora , or an S3-based data lake , are a great match to ML use cases since they tend to be much more scalable than traditional databases, both in terms of the data set sizes as well as query patterns. Software Development Layers.

ML 138

ML ML Data Scientist AWS 138

Flipboard

OCTOBER 9, 2023

AWS , GCP , Azure , DigitalOcean , etc.) Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science? You can use Docker to create, handle, manipulate, and run containers on your system locally. That’s not the case.

Machine Learning 116

Machine Learning Machine Learning Deep Learning Deep Learning 116

The MLOps Blog

OCTOBER 3, 2023

Mikiko Bazeley: Most people are really surprised to hear that my background in college was not computer science. For example, you can use BigQuery , AWS , or Azure. How awful are they?” How did you manage to jump from a more analytical, scientific type of role to a more engineering one?

ML 52

ML ML Data Scientist Machine Learning 52

Pickl AI

APRIL 2, 2024

Data science is the process of extracting the valuable minerals – the insights – that can transform your business. It’s a blend of statistics, computer science, and domain knowledge used to extract knowledge and create solutions from data. Data science for business leaders isn’t about becoming a coding pro.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52