Data Science Dojo

OCTOBER 31, 2024

Key Skills: Mastery in machine learning frameworks like PyTorch or TensorFlow is essential, along with a solid foundation in unsupervised learning methods. Stanford AI Lab recommends proficiency in deep learning, especially if working in experimental or cutting-edge areas.

Data Science 195

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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.

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Data Lakes Data Warehouse Big Data Big Data 135

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

DECEMBER 1, 2022

As we look ahead to 2022, there are four key trends that organizations should be aware of when it comes to big data: cloud computing, artificial intelligence, automated streaming analytics, and edge computing. Each of these trends will continue to shape the way companies use data in the coming years.

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Big Data Big Data Natural Language Processing Artificial Intelligence 145

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).

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Data Visualization Big Data Big Data Predictive Analytics 145

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 125

Smart Data Collective

FEBRUARY 20, 2022

Whether it’s data management, analytics, or scalability, AWS can be the top-notch solution for any SaaS company. Also, AWS data protection services provide encryption and key management, as well as threat detection for continuous monitoring and protection of your accounts and workloads. Messages and notification.

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AWS Cloud Computing Data Lakes Database 138

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 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

Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. These may range from Data Analytics projects for beginners to experienced ones.

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Analytics Analytics Big Data Big Data 40

Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

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

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

IBM Journey to AI blog

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. appeared first on IBM Blog.

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Machine Learning Machine Learning Data Science Big Data 70

ODSC - Open Data Science

FEBRUARY 6, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

Big Data Analytics 52

Big Data Analytics Big Data Analytics Big Data Big Data 52

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.

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Machine Learning Machine Learning Data Science AI 52

ODSC - Open Data Science

OCTOBER 17, 2023

Her interests lie in software testing, cloud computing, big data analytics, systems engineering, and architecture. Her recent area of expertise has been around machine learning and building data analytics for better and faster troubleshooting of performance problems and anomaly detection in production.

Data Science 98

Data Science Computer Science Computer Science Database 98

ODSC - Open Data Science

JANUARY 26, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

MAY 7, 2023

Data, analytics, AI, and robotics, today, the tech discussions revolve around these topics. One of them is the large volume of data that we are creating every day. Ways Facebook is Using Big Data Analysis of Text You would agree that a large volume of data is added to Facebook.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

SEPTEMBER 5, 2024

Introduction Data Science is revolutionising industries by extracting valuable insights from complex data sets, driving innovation, and enhancing decision-making. This roadmap aims to guide aspiring Azure Data Scientists through the essential steps to build a successful career.

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Azure Data Scientist Data Science Machine Learning 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

AWS Machine Learning Blog

APRIL 19, 2023

Streaming ingestion – An Amazon Kinesis Data Analytics for Apache Flink application backed by Apache Kafka topics in Amazon Managed Streaming for Apache Kafka (MSK) (Amazon MSK) calculates aggregated features from a transaction stream, and an AWS Lambda function updates the online feature store.

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ML ML Apache Kafka SQL 98

ODSC - Open Data Science

JANUARY 31, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. Microsoft Guidance steps in.

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Data Science Big Data Analytics Big Data Analytics Deep Learning 52

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. Chinese hospitals are already using data engineering to manage their supply chains.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 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.

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Artificial Intelligence Artificial Intelligence AI AI 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

DagsHub

NOVEMBER 11, 2024

Video : Movies, live streams, and CCTV footage combine visual and audio data, making them highly complex. Video analytics enable object detection, motion tracking, and behavioural analysis for security, traffic monitoring, or customer engagement insights.

AI 52

AI AI Data Lakes Database 52

Pickl AI

SEPTEMBER 11, 2024

Specialised Knowledge One key advantage of pursuing a master’s degree in Data Science is the ability to acquire specialised knowledge. Unlike a bachelor’s program, which provides a broad overview, a master’s program delves deep into specific areas such as predictive analytics, natural language processing, or Artificial Intelligence.

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Data Science Machine Learning Machine Learning Natural Language Processing 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

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

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Data Science Machine Learning Machine Learning Python 52

ODSC - Open Data Science

FEBRUARY 15, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. million human-written instructions for self-driving cars.

Data Science 52

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

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

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.

Big Data 147

Big Data Big Data Apache Hadoop Data Science 147

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.

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ML ML Machine Learning Machine Learning 52

Mlearning.ai

AUGUST 18, 2023

The next step involves applying analytical skills to discern patterns that can aid in diagnostic procedures. 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.

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 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