Smart Data Collective

DECEMBER 1, 2022

The growth in edge computing is mainly due to the increasing popularity of Internet of Things (IoT) devices. The two most common types of algorithms are deep learning and machine translation. Edge computing is processing data at the edge of a network, or on the device itself rather than in a centralized location.

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Big Data Big Data Natural Language Processing Artificial Intelligence 145

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 Warehouse.

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Data Lakes Data Warehouse Big Data Big Data 135

Applied Data Science

JANUARY 4, 2022

Source Self-supervision Self-supervision is a deep learning technique that could compete with Transformers for the most influential discovery of the past years. Statistical significance The answer is a concept that the deep learning community has been shoving under the carpet for a while now: statistical significance.

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ODSC - Open Data Science

APRIL 12, 2023

TDEngine At TDEngine they specialize in the ingestion, processing, and monitoring of the large amounts of data generated by the Internet of Things (IoT), Industrial IoT, and connected cars. Comet Comet’s mission is to provide support for enterprise deep learning at scale.

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Dataconomy

MAY 4, 2023

Apple’s ResearchKit, for example, leverages interactive apps and machine learning-based facial recognition to treat Asperger’s and Parkinson’s disease. IBM has recently partnered with Medtronic to decode, aggregate, and make diabetes and insulin data available in real-time based on crowdsourced information.

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Smart Data Collective

FEBRUARY 26, 2023

Tewari pointed out that “OpenAI’s GPT-3 or similar autoregressive language models that use deep learning to create human-like text.” Take the Internet of Things as an example. One poll found that 40% of AI art developers spent their time looking for utilitarian images.

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IBM Journey to AI blog

APRIL 22, 2024

Our approach includes applying AI, Internet of Things (IoT), and advanced data and automation solutions to empower this transition. Generative AI refers to deep-learning models that can take raw data and “learn” to generate statistically probable outputs when prompted.

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AI AI Internet of Things Deep Learning 97

Mlearning.ai

APRIL 10, 2023

Industrial Internet of Things (IIoT) The Constraints Within the area of Industry 4.0, In contrast, deep learning models with complex architectures (number of parameters and training processes) typically require more computation power in order to run. 4, center_box=(20, 5)) model = OPTICS().fit(x) Zhao, M.

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Clustering Internet of Things Algorithm Machine Learning 52

Dataconomy

AUGUST 21, 2023

While it builds upon the foundation of the Internet of Things (IoT), which brought us connected devices, ambient computing takes this concept further. IoT devices communicate over the internet, but ambient computing takes technology beyond connectivity.

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Artificial Intelligence Artificial Intelligence Internet of Things AI 91

Dataconomy

MAY 30, 2023

Amazon Go stores are cashierless supermarkets that utilize a combination of computer vision, sensor fusion, and deep learning algorithms to enable a seamless shopping experience. Customers can enter the store using their Amazon account, pick up items, and simply walk out without the need for traditional checkout.

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Algorithm Artificial Intelligence Artificial Intelligence Internet of Things 103

Pickl AI

FEBRUARY 14, 2023

Significantly, by leveraging technologies like deep learning and proprietary algorithms for analytics, Artivatic.ai Arya.ai One of the growing AI companies in India, Arya.ai, deploys Deep Learning solutions for the BFSI sector. Artivatic.ai Artivatic.ai

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AI AI Artificial Intelligence Artificial Intelligence 52

AWS Machine Learning Blog

OCTOBER 19, 2023

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII). Neelam Koshiya is an Enterprise Solutions Architect at AWS.

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Machine Learning Machine Learning ML ML 104

Pickl AI

JANUARY 3, 2024

Geographic Variations: The average salary of a Machine Learning professional in India is ₹12,95,145 per annum. Career Advancement: Professionals can enhance earning potential by acquiring in-demand skills like Natural Language Processing, Deep Learning, and relevant certifications aligned with industry needs.

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Machine Learning Machine Learning Natural Language Processing Deep Learning 52

Pickl AI

SEPTEMBER 3, 2024

ReLU is widely used in Deep Learning due to its simplicity and effectiveness in mitigating the vanishing gradient problem. Tanh (Hyperbolic Tangent): This function maps input values to a range between -1 and 1, providing a smooth gradient for learning.

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Heartbeat

MARCH 6, 2023

It can be used in a wide range of applications, especially when used with the Internet of Things. Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners.

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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

Heartbeat

OCTOBER 23, 2023

Image and Signal Processing: In medical imaging and signal processing, data scientists and machine learning engineers employ advanced algorithms to extract valuable information from images, such as CT scans, MRIs, and EKGs. We're committed to supporting and inspiring developers and engineers from all walks of life.

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Machine Learning Machine Learning Data Scientist Big Data Analytics 52

ML Review

FEBRUARY 26, 2018

Technology companies such as Google, Facebook, Microsoft, Amazon and Apple are at the forefront of personalized interactive products where intelligent human-computer interactions (IHCI) technology will continue to play a central role in automated messaging, task assistance and the Internet of Things.

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Dataconomy

AUGUST 6, 2023

Machine learning algorithms, particularly deep learning models, require immense computational power. A potential that we cannot ignore The possibilities enabled by parallel processing are as diverse as they are exciting. One of the most prominent domains benefiting from this technology is artificial intelligence.

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Heartbeat

JUNE 28, 2023

Small-size IoT (Internet of Things) devices and light machine learning models are becoming increasingly popular due to the growing demand for connected devices and intelligent automation in various industries. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Machine Learning Machine Learning Deep Learning Deep Learning 52

Pickl AI

SEPTEMBER 17, 2024

Some of the key future trends include: Increased Use of Deep Learning and Neural Networks As computing power and data availability continue to grow, we can expect to see more advanced Deep Learning models being applied to cybersecurity challenges, enabling even more accurate threat detection and prediction.

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AI AI Machine Learning Machine Learning 52

IBM Journey to AI blog

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Integrating conversational AI into the Internet of Things (IoT) also offers vast possibilities, enabling more intelligent and interactive environments through seamless communication between connected devices.

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Pickl AI

JANUARY 23, 2023

With Data Science, healthcare institutes have the power to harness tools like deep learning algorithms, which improve imaging accuracy by feeding the algorithm of the previous examples. These models can improvise with time and can give a more accurate outcome.

Data Science 52

Data Science Predictive Analytics Data Scientist Internet of Things 52

AWS Machine Learning Blog

MARCH 29, 2023

References Tercan H, “Machine learning and deep learning based predictive quality in manufacturing: a systematic review”, Journal of Intelligent Manufacturing, 2022. Meanwhile, he has been delivering AI courses at Amazon Machine Learning University and Oxford University. Hayat” means “life” in Turkish.

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ML ML AWS Machine Learning 85

AWS Machine Learning Blog

SEPTEMBER 1, 2023

The journey of providers FM providers need to train FMs, such as deep learning models. For the time being, there are two fine-tuning mechanisms: Fine-tuning – By using an FM and labeled data, a training job recalculates the weights and biases of the deep learning model layers.

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AI AI ML ML 120

Dataconomy

FEBRUARY 24, 2023

Existing and future technologies like big data, robotics, and the Internet of Things all have this as their major driver. Artificial intelligence (AI) is a multifaceted field of study, but recent advances in machine learning and deep learning are having a revolutionary effect across the board in the technology industry.

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AWS Machine Learning Blog

JANUARY 13, 2023

On the edge, the framework facilitates training and deployment of edge models to mobile phones and internet of things (IoT) devices. The FedML open-source library supports federated ML use cases for edge as well as cloud.

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Mlearning.ai

AUGUST 18, 2023

Utilizing Big Data, the Internet of Things, machine learning, artificial intelligence consulting , etc., On top of this, technologies like the Internet of Things (IoT) allow doctors to monitor patient’s health remotely. allows data scientists to revolutionize the entire sector.

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Data Science Data Scientist Internet of Things Apache Hadoop 52

AWS Machine Learning Blog

JANUARY 13, 2023

FedML supports several out-of-the-box deep learning algorithms for various data types, such as tabular, text, image, graphs, and Internet of Things (IoT) data. We call the data loader function for eICU data with the following code: elif dataset_name == "eicu": logging.info("load_data. Define the model.

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Smart Data Collective

JUNE 16, 2022

It is the ideal solution for contemporary cities that wish to leverage the power of the internet of things while providing possible advantages to their residents. . Deep Learning Technology has started being used increasingly in managing parking areas. Learn more here. What is Deep Learning Technology.

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ODSC - Open Data Science

JULY 19, 2023

Additional architecture tailored for Azure ML + Spark and IoT (Internet of Things) Edge scenarios are in development. The repository also features architecture specifically designed for Computer Vision (CV) and Natural Language Processing (NLP) use cases.

Machine Learning 52

Machine Learning Machine Learning Azure Data Science 52

Pickl AI

JULY 20, 2023

IoT (Internet of Things) Analytics Projects: IoT analytics involves processing and analyzing data from IoT devices to gain insights into device performance, usage patterns, and predictive maintenance. Image Recognition with Deep Learning: Use Python with TensorFlow or PyTorch to build an image recognition model (e.g.,

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ODSC - Open Data Science

JULY 25, 2023

Internet of Things (IoT) and the Edge: IoT is making it possible for many more devices to be connected, generate, and process data at the source. This can make it less necessary for companies to have their own data center. This means that data can be processed at the edge of the network, near the device itself.

AI 52

AI AI Cloud Computing Artificial Intelligence 52

Dataconomy

JANUARY 9, 2020

From wild speculation that flying cars will become the norm to robots that will be able to tend to our every need, there is lots of buzz about how AI, Machine Learning, and Deep Learning will change our lives. However, at present, it seems like a far-fetched future.

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Pickl AI

JULY 31, 2023

Deep Learning A subset of machine learning, Deep Learning involves neural networks with multiple layers that can automatically learn representations of data, leading to more complex and abstract reasoning. Autonomous vehicles and drones are examples of AI systems with decision-making capabilities.

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