Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon. Knowledge is power. Sharing knowledge is the key to unlocking that power.”―

Data Science 345

Data Science Analytics Analytics Apache Hadoop 345

Smart Data Collective

AUGUST 28, 2021

On the other hand, a data scientist may require access to unstructured data to detect patterns or build a deep learning model, which means that a data lake is a perfect fit for them. Data lakes have become quite popular due to the emerging use of Hadoop, which is an open-source software.

Data Lakes 140

Data Lakes Data Warehouse ETL Data Scientist 140

Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? The post Data Science Blogathon 28th Edition appeared first on Analytics Vidhya. If all of these describe you, then this Blogathon announcement is for you!

Data Science 328

Data Science Analytics Analytics Hadoop 328

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Tools and frameworks like Scikit-Learn, TensorFlow, and Keras are often covered. It will continue to make them a favorable choice in this fast-paced digital world.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Mlearning.ai

JANUARY 28, 2023

From Sale Marketing Business 7 Powerful Python ML For Data Science And Machine Learning need to be use. The data-driven world will be in full swing. With the growth of big data and artificial intelligence, it is important that you have the right tools to help you achieve your goals. To perform data analysis 6.

Machine Learning 52

Machine Learning Machine Learning Data Science ML 52

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? Machine learning and deep learning are both subsets of AI.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

AWS Machine Learning Blog

DECEMBER 18, 2023

SageMaker Canvas supports a number of use cases, including time-series forecasting , which empowers businesses to forecast future demand, sales, resource requirements, and other time-series data accurately. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

Clustering 121

Clustering AWS Database ML 121

Pickl AI

MAY 29, 2024

Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation. What does a typical Data Science syllabus cover?

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

AWS Machine Learning Blog

FEBRUARY 13, 2024

With a strong background in computer vision, data science, and deep learning, he holds a postgraduate degree from IIT Bombay. He has worked on building enterprise-grade applications, building data platforms in multiple organizations and reporting platforms to streamline decisions backed by data.

AWS 131

AWS AI AI ML 131

Pickl AI

NOVEMBER 28, 2024

For example, in neural networks, data is represented as matrices, and operations like matrix multiplication transform inputs through layers, adjusting weights during training. Without linear algebra, understanding the mechanics of Deep Learning and optimisation would be nearly impossible.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

JANUARY 7, 2025

Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on. Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

JULY 20, 2023

Defining clear objectives and selecting appropriate techniques to extract valuable insights from the data is essential. Here are some project ideas suitable for students interested in big data analytics with Python: 1. Here are a few business analytics big data projects: 1. ImageNet).

Analytics 40

Analytics Analytics Big Data Big Data 40

DagsHub

NOVEMBER 11, 2024

These vector databases store complex data by transforming the original unstructured data into numerical embeddings; this is enabled through deep learning models. As reiterated earlier, embeddings take the critical components of various kinds of data, like text, images, and audio, and project them into one vector space.

AI 52

AI AI Data Lakes Database 52

DagsHub

OCTOBER 23, 2024

Data Lakes Data lakes are centralized repositories designed to store vast amounts of raw, unstructured, and structured data in their native format. They enable flexible data storage and retrieval for diverse use cases, making them highly scalable for big data applications.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 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

Pickl AI

JUNE 19, 2024

For instance, courses focusing on big data might require knowledge of Hadoop or Spark, while those emphasizing machine learning might delve into deep learning frameworks like TensorFlow or PyTorch.

Data Science 52

Data Science Data Scientist Hypothesis Testing Natural Language Processing 52

DagsHub

AUGUST 23, 2024

It provides visibility into data flows, offers various data quality checks (including custom rules), and inspects pipeline performance (job execution times, data volumes, and error rates). With this tool, you can implement and monitor data quality rules across different data sources.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Data Science Dojo

MAY 24, 2024

For example, predictive maintenance in manufacturing uses machine learning to anticipate equipment failures before they occur, reducing downtime and saving costs. Deep Learning Deep learning is a subset of machine learning based on artificial neural networks, where the model learns to perform tasks directly from text, images, or sounds.

Deep Learning 195

Deep Learning Deep Learning Machine Learning Machine Learning 195

Data Science Dojo

AUGUST 30, 2023

From decision trees and neural networks to regression models and clustering algorithms, a variety of techniques come under the umbrella of machine learning. Big data processing With the increasing volume of data, big data technologies have become indispensable for Applied Data Science.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Pickl AI

APRIL 2, 2024

Understanding Data Structured Data: Organized data with a clear format, often found in databases or spreadsheets. Unstructured Data: Data without a predefined structure, like text documents, social media posts, or images. Data Cleaning: Process of identifying and correcting errors or inconsistencies in datasets.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52