Smart Data Collective

SEPTEMBER 23, 2020

Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

Data Lakes 135

Data Lakes Data Warehouse Big Data Big Data 135

Data Science Blog

MARCH 14, 2023

Von Data Science spricht auf Konferenzen heute kaum noch jemand und wurde hype-technisch komplett durch Machine Learning bzw. Big Data Analytics erreicht die nötige Reife Der Begriff Big Data war schon immer etwas schwammig und wurde von vielen Unternehmen und Experten schnell auch im Kontext kleinerer Datenmengen verwendet.

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Big Data Big Data Apache Hadoop Data Science 147

ODSC - Open Data Science

MARCH 6, 2023

Big data analytics is evergreen, and as more companies use big data it only makes sense that practitioners are interested in analyzing data in-house. Deep learning is a fairly common sibling of machine learning, just going a bit more in-depth, so ML practitioners most often still work with deep learning.

Machine Learning 116

Machine Learning Machine Learning Data Science Deep Learning 116

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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AWS Machine Learning Blog

OCTOBER 5, 2023

He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. Yida Wang is a principal scientist in the AWS AI team of Amazon.

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AWS Machine Learning Machine Learning Deep Learning 116

Smart Data Collective

OCTOBER 13, 2021

As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields).

Data Visualization 145

Data Visualization Big Data Big Data Predictive Analytics 145

ODSC - Open Data Science

FEBRUARY 8, 2024

Deep Learning with PyTorch and TensorFlow Dr. Jon Krohn | Chief Data Scientist | Nebula.io Jon Krohn, for an immersive introduction to Deep Learning that brings high-level theory to life with interactive examples featuring all three of the principal Python libraries, PyTorch, TensorFlow 2, and Keras.

Big Data Analytics 52

Big Data Analytics Big Data Analytics Deep Learning Deep Learning 52

Smart Data Collective

DECEMBER 1, 2022

The two most common types of algorithms are deep learning and machine translation. Natural Language Processing (NLP) algorithm techniques require grammar rules to recognize and obtain data from every sentence. This technology is part of artificial intelligence that operates to develop communication between humans and computers.

Big Data 145

Big Data Big Data Natural Language Processing Artificial Intelligence 145

Smart Data Collective

FEBRUARY 20, 2022

The analysis of tons of data for your SaaS business can be extremely time-consuming, and it could even be impossible if done manually. Rather, AWS offers a variety of data movement, data storage, data lakes, big data analytics, log analytics, streaming analytics, and machine learning (ML) services to suit any need.

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AWS Cloud Computing Data Lakes Database 138

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Pickl AI

AUGUST 9, 2024

Additionally, students should grasp the significance of Big Data in various sectors, including healthcare, finance, retail, and social media. Understanding the implications of Big Data analytics on business strategies and decision-making processes is also vital.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

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

ODSC - Open Data Science

APRIL 4, 2024

Data Analytics in the Age of AI, When to Use RAG, Examples of Data Visualization with D3 and Vega, and ODSC East Selling Out Soon Data Analytics in the Age of AI Let’s explore the multifaceted ways in which AI is revolutionizing data analytics, making it more accessible, efficient, and insightful than ever before.

Data Visualization 52

Data Visualization Analytics Analytics Big Data Analytics 52

ODSC - Open Data Science

FEBRUARY 6, 2024

LLMs Meet Google Cloud: A New Frontier in Big Data Analytics Mohammad Soltanieh-ha, PhD | Clinical Assistant Professor | Boston University Dive into the world of cloud computing and big data analytics with Google Cloud’s advanced tools and big data capabilities.

Big Data Analytics 52

Big Data Analytics Big Data Analytics Big Data Big Data 52

IBM Journey to AI blog

JULY 6, 2023

Healthcare companies are using data science for breast cancer prediction and other uses. One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time. Machine learning and deep learning are both subsets of AI.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

ODSC - Open Data Science

OCTOBER 17, 2023

Her interests lie in software testing, cloud computing, big data analytics, systems engineering, and architecture. Tuli Nivas is a Software Engineering Architect at Salesforce with extensive experience in design and implementation of test automation and monitoring frameworks.

Data Science 98

Data Science Computer Science Computer Science Database 98

ODSC - Open Data Science

OCTOBER 22, 2024

NVIDIA: Powering the AI Revolution NVIDIA is a global leader in AI computing, designing GPUs and software that accelerate deep learning, machine learning, and high-performance computing. This impressive lineup includes: DataRobot: A leader in automated machine learning platforms, helping businesses deploy AI at scale.

Machine Learning 52

Machine Learning Machine Learning Data Science AI 52

Heartbeat

OCTOBER 25, 2023

e) Big Data Analytics: The exponential growth of biological data presents challenges in storing, processing, and analyzing large-scale datasets. Traditional computational infrastructure may not be sufficient to handle the vast amounts of data generated by high-throughput technologies.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

ODSC - Open Data Science

JANUARY 26, 2024

It will also feature even more hands-on training sessions, expert-led workshops, and tutorials on topics like machine learning, NLP and LLMs, data engineering, big data analytics, MLOps, generative AI, and more for our in-person attendees.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

MAY 7, 2023

It’s actually Big Data technologies. For this, the Deep Learning application “DeepFace” is adopted. Empowering Connections: Big Data Analytics At Facebook Big Data Analytics certainly plays an integral role in enhancing the customer experience. Thus aiding the process of tagging.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

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. Movie Recommendation System: Use Python and collaborative filtering techniques (e.g., ImageNet).

Analytics 40

Analytics Analytics Big Data Big Data 40

ODSC - Open Data Science

JANUARY 31, 2024

Connect with some of the most innovative people and ideas in the world of data science, while learning first-hand from core practitioners and contributors.

Data Science 52

Data Science Big Data Analytics Big Data Analytics Deep Learning 52

How to Learn Machine Learning

APRIL 23, 2023

It is a waste of time in machine learning and in adopting artificial intelligence in general if companies allow themselves to be dragged by failures from its past projects. By quickly acting after failure, companies reach the goal of building a solid machine learning strategy ideal to withstand changes.

Machine Learning 52

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 52

IBM Journey to AI blog

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.  The applications of AI in commerce are vast and varied.

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AI AI Algorithm Machine Learning 81

phData

AUGUST 11, 2023

Capturing and maintaining data on a large population can help doctors chart the best course of action according to their previous diagnoses. The use of deep learning and machine learning in healthcare is also increasing. Data engineering in research helped to study vaccines better.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 5, 2024

This allows Data Scientists to bring their existing code, libraries, and workflows into the Azure ecosystem without disruption. Support for Deep Learning Frameworks It integrates with TensorFlow, PyTorch, and other Deep Learning frameworks, providing scalable infrastructure for training and deploying complex models.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

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

Pickl AI

SEPTEMBER 11, 2024

It should cover many essential topics, including Statistics, Machine Learning, Data Mining , Big Data Analytics, and visualisation. Electives focusing on emerging technologies such as Artificial Intelligence, Deep Learning, and Natural Language Processing are also crucial.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

Mlearning.ai

AUGUST 18, 2023

Data science in healthcare allows physicians to access patients’ health data, see the change over time, and tweak the treatment plan if something goes wrong. Utilizing big data analytics allows medical professionals to take advantage of historical information and get valuable insights.

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 52

ODSC - Open Data Science

FEBRUARY 15, 2024

Connect with some of the most innovative people and ideas in the world of data science, while learning first-hand from core practitioners and contributors.

Data Science 52

Data Science Natural Language Processing Big Data Analytics Big Data Analytics 52

Pickl AI

APRIL 10, 2023

So, if you are eyeing your career in the data domain, this blog will take you through some of the best colleges for Data Science in India. There is a growing demand for employees with digital skills The world is drifting towards data-based decision making In India, a technology analyst can make between ₹ 5.5 Lakhs to ₹ 11.0

Data Science 52

Data Science Machine Learning Machine Learning Python 52

AWS Machine Learning Blog

APRIL 19, 2023

About the Authors Mark Roy is a Principal Machine Learning Architect for AWS, helping customers design and build AI/ML solutions. Mark’s work covers a wide range of ML use cases, with a primary interest in feature stores, computer vision, deep learning, and scaling ML across the enterprise.

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ML ML Apache Kafka SQL 87

Pickl AI

JANUARY 12, 2023

Additionally, it involves learning the mathematical and computational tools that form the core of Data Science. Besides, you will also learn how to use the tools that will eventually help in making data-driven decisions.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

The MLOps Blog

AUGUST 11, 2023

Standard ML pipeline | Source: Author Advantages and disadvantages of directed acyclic graphs architecture Using DAGs provides an efficient way to execute processes and tasks in various applications, including big data analytics, machine learning, and artificial intelligence, where task dependencies and the order of execution are crucial.

ML 52

ML ML Machine Learning Machine Learning 52

Dataconomy

FEBRUARY 11, 2025

AI summers, such as those driven by advancements in deep learning, increased computational power, and big data analytics, have repeatedly revived interest and funding.

AI 113

AI AI Big Data Analytics Big Data Analytics 113

Dataconomy

FEBRUARY 26, 2025

This capability bridges various disciplines, leveraging techniques from statistics, machine learning, and artificial intelligence. Some key areas include: Big Data analytics: It helps in interpreting vast amounts of data to extract meaningful insights.

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Support Vector Machines Machine Learning Machine Learning Decision Trees 91