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Using Cloudera Machine Learning to Build a Predictive Maintenance Model for Jet Engines

Cloudera

Running a large commercial airline requires the complex management of critical components, including fuel futures contracts, aircraft maintenance and customer expectations. Airlines, in just the U.S. Airlines typically operate on very thin margins, and any schedule delay immediately angers or frustrates customers. Introduction.

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WestCap and Peter Thiel-backed FLYR Labs closes $150M Series C

TechCrunch

Airlines have a relatively straightforward goal — getting people in seats — but they’ve traditionally relied on inefficient and outdated statistical modeling methods to predict what prices and other conditions will sell tickets. Enter FLYR Labs. — the model will get smarter over time, FLYR says.

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Flight Price Predictor: Training Models to Pinpoint the Best Time for Booking

Altexsoft

Pricing in the airline industry is often compared to a brain game between carriers and passengers where each party pursues the best rates. How dynamic pricing in the airline industry works. Airlines employ the technology to forecast rates of competitors and adjust their pricing strategies accordingly. Internal factors include.

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10 emerging innovations that could redefine IT

CIO

Once wild and seemingly impossible notions such as large language models, machine learning, and natural language processing have gone from the labs to the front lines. The biggest worries are coming from websites that recognize how their data may be used to train AI models.

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Machine Learning Metrics: How to Measure the Performance of a Machine Learning Model

Altexsoft

Choosing the machine learning path when developing your software is half the success. Yes, it brings automation, so widely discussed machine intelligence, and other awesome perks. So, how would you measure the success of a machine learning model? So, how would you measure the success of a machine learning model?

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Is Conversational AI Right for Your Business?

Trigent

Conversational AI is an interesting blend of tech Natural Language Processing (NLP), machine learning (ML), deep learning, contextual awareness, and Art. For Conversational AI voice bots, ASR (Automatic Speech Recognition) and TTS (Text to Speech) routines need to be integrated with necessary customization and training.

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Data Science use cases & tools

Apiumhub

Machine Learning. Machine learning is the backbone of data science. Modeling is also a part of ML and involves identifying which algorithm is the most suitable to solve a given problem and how to train these models. Data Science pillars. Healthcare. Cybersecurity.

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