Smart Data Collective

MARCH 23, 2022

AI refers to an advanced machine or computer technology that simulates human intelligence processes, powered by several applications such as natural language processing (NLP), machine vision, speech recognition, and expert systems. What Is Artificial Intelligence?

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Data Science Connect

JULY 26, 2023

Using AI for Anomaly Detection Artificial Intelligence (AI) algorithms can be employed to detect anomalies in energy consumption and system behavior, indicating potential security breaches or inefficiencies in sustainable operations.

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Data Science Connect

JULY 24, 2023

By leveraging AI and machine learning algorithms, they can analyze vast amounts of environmental data, weather patterns, and historical records to provide farmers with real-time insights and predictive analytics for informed decision-making. Data scientists play a pivotal role in designing and implementing advanced climate data systems.

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Data Science Connect

JULY 23, 2023

The automotive industry is on the brink of a technological revolution, powered by the seamless integration of the Internet of Things (IoT). The sheer volume of data generated by IoT devices poses a significant challenge in terms of data analytics and processing.

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Dataconomy

SEPTEMBER 4, 2023

Predictive analytics: Predictive analytics leverages historical data and statistical algorithms to make predictions about future events or trends. It’s particularly valuable for forecasting demand, identifying potential risks, and optimizing processes.

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Applied Data Science

JANUARY 4, 2022

Initially introduced for Natural Language Processing (NLP) applications like translation, this type of network was used in both Google’s BERT and OpenAI’s GPT-2 and GPT-3. The immense computational complexity of recent algorithms has forced their creators to train them only a handful of times, in many cases just once.

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Mlearning.ai

APRIL 10, 2023

3 feature visual representation of a K-means Algorithm. Essentially, the clustering algorithm is grouping data points together without any prior knowledge or guidance to discover hidden patterns or unusual data groupings without the need for human interference.

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Mlearning.ai

JULY 21, 2023

By harnessing the power of data and algorithms, machine learning enables apps to optimize their operations, improve decision-making, and deliver a superior user experience. We’ll discuss how machine learning algorithms aid in fraud detection and prevention, ensuring the security of transactions.

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Dataconomy

AUGUST 21, 2023

This is the promise of ambient computing—a technology where an algorithm knows you so well that it anticipates your needs before you’re even aware of them. While it builds upon the foundation of the Internet of Things (IoT), which brought us connected devices, ambient computing takes this concept further.

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ODSC - Open Data Science

JANUARY 26, 2023

Inaccurate inferences may occur because dissimilar data points confuse the algorithms if they’re too small or large. However, it is worth the time since it will deliver the most prominent benefit for whatever technology it informs — whether it’s natural language processing with a chatbot or AI in Internet of Things (IoT) tech.

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AWS Machine Learning Blog

JANUARY 13, 2023

Because ML algorithms are often not adequate in protecting the privacy of patient-level data, there is a growing interest among HCLS partners and customers to use privacy-preserving mechanisms and infrastructure for managing and analyzing large-scale, distributed, and sensitive data. [1].

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Pickl AI

SEPTEMBER 3, 2024

Here are some core responsibilities and applications of ANNs: Pattern Recognition ANNs excel in recognising patterns within data , making them ideal for tasks such as image recognition, speech recognition, and natural language processing.

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Pickl AI

AUGUST 1, 2024

Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms. Understanding Deep Learning Engineer A Deep Learning engineer is primarily responsible for creating and optimising algorithms that enable machines to learn from data.

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Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

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IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. ML algorithms understand language in the NLU subprocesses and generate human language within the NLG subprocesses.

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Pickl AI

JANUARY 3, 2024

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. Geographic Variations: The average salary of a Machine Learning professional in India is ₹12,95,145 per annum. from 2023 to 2030.

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Pickl AI

SEPTEMBER 17, 2024

Summary : AI is transforming the cybersecurity landscape by enabling advanced threat detection, automating security processes, and adapting to new threats. It leverages Machine Learning, natural language processing, and predictive analytics to identify malicious activities, streamline incident response, and optimise security measures.

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Pickl AI

JULY 20, 2023

Techniques like regression analysis, time series forecasting, and machine learning algorithms are used to predict customer behavior, sales trends, equipment failure, and more. Use machine learning algorithms to build a fraud detection model and identify potentially fraudulent transactions.

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Pickl AI

JULY 14, 2023

Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications. RL algorithms, such as Deep Q-Networks (DQNs) and AlphaGo, demonstrated significant accomplishments in game playing and control tasks.

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How to Learn Machine Learning

DECEMBER 2, 2022

The technology increases diagnostic accuracy and monitors disease progression using Machine Learning, Natural Language Processing, and Neural Networks. AI-powered financial institutions reject your loan applications due to the bias unintentionally loaded into their algorithms.

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IBM Journey to AI blog

JULY 11, 2024

AI allows businesses to process large amounts of data in real time, anticipate market trends, optimize logistics, and perform routing and scheduling based on changing conditions. Predictive maintenance AI algorithms can analyze sensor data and historical maintenance records to predict equipment failure.

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Pickl AI

JULY 23, 2023

Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases. It requires sophisticated tools and algorithms to derive meaningful patterns and trends from the sheer magnitude of data.

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Pickl AI

DECEMBER 2, 2024

For example, financial institutions utilise high-frequency trading algorithms that analyse market data in milliseconds to make investment decisions. Internet of Things (IoT): Devices such as sensors, smart appliances, and wearables continuously collect and transmit data.

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Pickl AI

NOVEMBER 25, 2024

For example, financial institutions utilise high-frequency trading algorithms that analyse market data in milliseconds to make investment decisions. Internet of Things (IoT): Devices such as sensors, smart appliances, and wearables continuously collect and transmit data.

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IBM Journey to AI blog

JULY 11, 2024

AI allows businesses to process large amounts of data in real time, anticipate market trends, optimize logistics, and perform routing and scheduling based on changing conditions. Predictive maintenance AI algorithms can analyze sensor data and historical maintenance records to predict equipment failure.

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Pickl AI

JANUARY 16, 2024

Predictive Modeler Harnessing the power of algorithms to forecast future trends, aiding businesses in strategic decision-making. IoT Data Analyst Analysing data generated by Internet of Things (IoT) devices, extracting meaningful patterns and trends for improved efficiency and decision-making. Value in 2021 – $1.12

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Mlearning.ai

AUGUST 18, 2023

Utilizing Big Data, the Internet of Things, machine learning, artificial intelligence consulting , etc., Considering the human body generates two terabytes of data on a daily basis, from brain activity to muscle performance, scientists have a lot of information to collect and process.

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Heartbeat

JUNE 23, 2023

Time series analysis has become increasingly relevant for a variety of industries, including banking, healthcare, and retail, as big data and the internet of things (IoT) have grown in popularity. Preprocessing involves cleaning, transforming, and restructuring data into a more suitable format for deep learning algorithms.

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AWS Machine Learning Blog

JANUARY 20, 2023

A trusted leader in AI, Internet of Things (IoT), customer experience, and network and workflow management, CCC delivers innovations that keep people’s lives moving forward when it matters most. The challenge CCC processes more than $1 trillion claims transactions annually.

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Pickl AI

JULY 31, 2023

Examples of narrow AI include virtual personal assistants like Siri or Alexa, recommendation systems used by online platforms, and algorithms used in autonomous vehicles for specific driving tasks. Machine Learning AI systems often employ machine learning algorithms to learn from data and improve their performance over time.

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Pickl AI

JUNE 18, 2024

AI algorithms in Power BI can sift through vast datasets, identifying unusual patterns that might escape human attention. The Internet of Things (IoT) generates vast amounts of data from sensors and connected devices. By analyzing historical data and incorporating external factors, predictive models can anticipate future trends.

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IBM Journey to AI blog

FEBRUARY 9, 2024

The incoming generation of interdisciplinary models, comprising proprietary models like OpenAI’s GPT-4V or Google’s Gemini, as well as open source models like LLaVa, Adept or Qwen-VL, can move freely between natural language processing (NLP) and computer vision tasks.

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