Pickl AI

JANUARY 16, 2024

Summary: The blog delves into the 2024 Data Analyst career landscape, focusing on critical skills like Data Visualisation and statistical analysis. It identifies emerging roles, such as AI Ethicist and Healthcare Data Analyst, reflecting the diverse applications of Data Analysis.

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Pickl AI

JUNE 18, 2024

Summary: This blog dives into the most promising Power BI projects, exploring advanced data visualization, AI integration, IoT & blockchain analytics, and emerging technologies. Discover best practices for successful implementation and propel your organization towards data-driven success.

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Mlearning.ai

APRIL 10, 2023

With the emergence of data science and AI, clustering has allowed us to view data sets that are not easily detectable by the human eye. Thus, this type of task is very important for exploratory data analysis. Industrial Internet of Things (IIoT) The Constraints Within the area of Industry 4.0, Zhao, M.

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Pickl AI

JUNE 4, 2024

By establishing a well-defined data collection and management strategy, organizations in the sustainable energy sector can harness the power of data to optimize energy production and consumption, drive efficiency improvements, and ultimately contribute to a cleaner energy future.

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Pickl AI

SEPTEMBER 13, 2024

For example, Google Flu Trends used search query data to estimate flu activity in real-time, allowing public health officials to respond more effectively. Predictive Analytics Predictive analytics models can forecast the spread of infectious diseases by analysing historical data and identifying patterns.

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Pickl AI

JUNE 29, 2023

Data Analysis is significant as it helps accurately assess data that drive data-driven decisions. Different tools are available in the market that help in the process of analysis. It is a powerful and widely-used platform that revolutionises how organisations analyse and derive insights from their data.

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Pickl AI

OCTOBER 1, 2024

By analysing data on demand patterns and transportation routes, AI systems can reduce waste and improve efficiency. Example: Predictive Analytics for Supply Chains IBM Food Trust employs blockchain technology combined with AI analytics to enhance transparency in food supply chains.

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Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters.

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Pickl AI

JUNE 6, 2024

Enter predictive modeling , a powerful tool that harnesses the power of data to anticipate what tomorrow may hold. What is Predictive Modeling? Predictive modeling is a statistical technique that uses Data Analysis to make informed forecasts about future events.

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The MLOps Blog

FEBRUARY 5, 2023

We will also get familiar with tools that can help record this data and further analyse it. In the later part of this article, we will discuss its importance and how we can use machine learning for streaming data analysis with the help of a hands-on example. What is streaming data?

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Pickl AI

SEPTEMBER 3, 2024

Explainable AI (XAI) aims to provide insights into how neural networks make decisions, helping stakeholders understand the reasoning behind predictions and classifications. Edge Computing With the rise of the Internet of Things (IoT), edge computing is becoming more prevalent.

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Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters.

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Pickl AI

JULY 29, 2024

Log Analysis These are well-suited for analysing log data from various sources, such as web servers, application logs, and sensor data, to gain insights into user behaviour and system performance. Organisations that require low-latency data analysis may find Hadoop insufficient for their needs.

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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.

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Pickl AI

JULY 20, 2023

It involves deeper analysis and investigation to identify the root causes of problems or successes. Root cause analysis is a typical diagnostic analytics task. 3. Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes.

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Pickl AI

OCTOBER 3, 2024

Applications include: Customer Segmentation: Marketers can use no-code platforms to analyse customer data and segment audiences based on behaviour and preferences, allowing for more targeted marketing strategies. The post No-code AI: A Detailed Analysis appeared first on Pickl.AI. What are Some Examples of No-code AI Applications?

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Pickl AI

AUGUST 24, 2023

Local Data Governance: Edge Computing empowers organizations to adhere to data governance regulations by enabling them to process and store data locally, ensuring compliance with data sovereignty laws. Support for IoT Growth: As the Internet of Things (IoT) continues to expand, Edge Computing is a natural fit.

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Pickl AI

JULY 31, 2023

Endor Protocol (EDR) A predictive analytics platform that allows businesses to access AI-powered insights without exposing raw data, thanks to Blockchain-based privacy solutions. Effect.ai (EFX) A decentralized AI platform that connects businesses and developers, offering services for AI training and data processing.

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