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A collection of awesome Machine Learning software, libraries, Learning Tutorials, documents, books, resources and interesting stuff in ML - machine-learning-collection/README.md at main · exajobs/machine-learning-collection
Learning Hiring Preferences: The AI Behind LinkedIn Jobs LinkedIn 2019 The Secret Sauce Behind Search Personalisation Gojek 2019 Neural Code Search: ML-based Code Search Using Natural Language Queries Facebook 2019 Aggregating Search Results from Heterogeneous Sources via Reinforcement Learning (Paper) Alib...
The AWS Machine Learning — Specialty MLS-C01 Certification is intended for individuals who are responsible for developing data science or applied machine learning projects on the AWS Cloud. This specialty certification is quite different from any other AWS exam. If you already have prior experience ...
Remote jobs with Apache Livy Debug Apache Spark jobs remotely with IntelliJ through VPN Apache Spark streaming Apache Spark and Machine Learning Predict food inspection results Analyze website logs Use with Microsoft Cognitive Toolkit Create an Apache Spark machine learning pipeline Analyze big data Manag...
hybrid workforces. One of their key assumptions driving the forecast is that “by the end of 2026, the democratization of technology, digitization, and automation of work will increase the total available market of fully remote and hybrid workers to 64% of all employees, up from 52% in 2021...
While artificial intelligence limits itself to processing data for a better outcome, machine intelligence, in general, also caters to capturing and transforming data with eventual processing by learning algorithms. Machine vision is one such subfield where machine intelligence is applied for data captured...
Earth fissures are potential hazards that often cause severe damage and affect infrastructure, the environment, and socio-economic development. Owing to the complexity of the causes of earth fissures, the prediction of earth fissures remains a challengin
Kirill Eremenko joins Jon Krohn for another exclusive, in-depth teaser for a new course just released on the SuperDataScience platform, “Machine Learning Level 2”. Kirill walks listeners through why decision trees and random forests are fruitful for bu
a fleet management system or different type of devices, it is recommended to use one of the IoT platforms in the cloud or locally (AWS, Microsoft, Particle, IBM, Oracle, OpenRemote, and others). Stay tuned.. Posted in hardware, innovation, iot, raspberry pi Feb27 Taming the beast – ...