Pickl AI

DECEMBER 25, 2024

Key Takeaways Business Analytics targets historical insights; Data Science excels in prediction and automation. Business Analytics requires business acumen; Data Science demands technical expertise in coding and ML. With added skills, professionals can shift between Business Analytics and Data Science. Masters or Ph.D.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Mlearning.ai

MAY 23, 2023

Knowledge of visualization libraries, such as Matplotlib, Seaborn, or ggplot, and understanding design principles can help in creating compelling visual representations of data. However, many data scientists also hold advanced degrees such as a Master’s or Ph.D. in these fields.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. What is Unstructured Data?

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Mlearning.ai

MAY 16, 2023

It involves breaking down the data into smaller chunks that can be processed in parallel across multiple nodes, and then combining the results of those processing tasks to produce a final output. Batch Processing Design Pattern The batch Processing Design Pattern is commonly used for processing large amounts of data in batches.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. link] Tables The table in GCP BigQuery is a collection of rows and columns that can store and manage massive amounts of data.

SQL 52

SQL Database Apache Hadoop Data Science 52

Pickl AI

MAY 31, 2023

Machine Learning: Data Science aspirants need to have a good and concise understanding on Machine Learning algorithms including both supervised and unsupervised learning. Proficiency in ML is understood when these are not just present in the aspirant in conceptual ways but also in terms of its applications in solving business problems.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Mlearning.ai

AUGUST 18, 2023

As a discipline that includes various technologies and techniques, data science can contribute to the development of new medications, prevention of diseases, diagnostics, and much more. Utilizing Big Data, the Internet of Things, machine learning, artificial intelligence consulting , etc.,

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 52