Top 14 Machine Learning Research Papers Of 2019


https://bit.ly/2ExLslR

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XGBoost: An Intuitive Explanation
Ashutosh Nayak :
https://towardsdatascience.com/xgboost-an-intuitive-explanation-88eb32a48eff
#MachineLearning #DataScience

MIT lecture series on deep learning in 2019
MIT lecture series on deep learning:Basics:
https://www.youtube.com/watch?v=O5xeyoRL95U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

MIT lecture series on deep learning: State of the Art:
https://www.youtube.com/watch?v=53YvP6gdD7U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

MIT lecture series on deep learning: Introduction to Deep RL:
https://www.youtube.com/watch?v=zR11FLZ-O9M&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

Find The Most Updated and Free Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Mathematics, Python Programming Resources

https://www.marktechpost.com/free-resources/

GL2vec: Graph Embedding Enriched by Line Graphs with Edge Features

Code: https://github.com/benedekrozemberczki/karateclub

Paper: https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1

https://karateclub.readthedocs.io

Named Entity Recognition (NER) from social media posts is a challenging task. User-generated content which forms the nature of social media, is noisy and contains grammatical and linguistic errors. This noisy content makes it much harder for tasks such as named entity recognition. However some applications like automatic journalism or information retrieval from social media, require more information about entities mentioned in groups of social media posts. Conventional methods applied to structured and well typed documents provide acceptable results while compared to new user generated media, these methods are not satisfactory. One valuable piece of information about an entity is the related image to the text. Combining this multimodal data reduces ambiguity and provides wider information about the entities mentioned. In order to address this issue, we propose a novel deep learning approach utilizing multimodal deep learning. Our solution is able to provide more accurate results on named entity recognition task. Experimental results, namely the precision, recall and F1 score metrics show the superiority of our work compared to other state-of-the-art NER solutions.

https://arxiv.org/abs/2001.06888

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Decision trees are extremely fast when it comes to classify unknown records. Watch this video to know how Decision Tree algorithm works, in an easy way - http://bit.ly/2Ggsb9l

#DataScience #MachineLearning #AI #ML #ReinforcementLearning #Analytics #CloudComputing #Python #DeepLearning #BigData #Hadoop

a new NLU benchmark for testing the ability of models to break down a question into the required steps for computing its answer. https://allenai.github.io/Break/ A work by Tomer Wolfson, accepted to TACL 2020.

Very informative model of the potential spread of nCov across the global aviation network.
Includes a nice explanation of the rationale. Remarkable how well aligned the probabilities are with the observed cases. http://rocs.hu-berlin.de/corona/

We are looking for full time Data Analyst working with our industry partners, as well as contributing to our university's world class science and research.

https://jobs.illinois.edu/academic-job-board/job-details?jobID=125801&job=data-analyst-national-center-for-supercomputing-applications-125801

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https://medium.com/sfu-big-data/why-so-many-different-clustering-algorithms-2fd94906c668
Why so many different clustering algorithms?
Cluster analysis is an unsupervised learning task that aims to divide objects into groups based on their similarity.

🔥 As you know ML has proven its importance in many fields, like computer vision, NLP, reinforcement learning, adversarial learning, etc .. Unfortunately, there is a little work to make machine learning accessible for Arabic-speaking people. Arabic language has many complicated features compared to other languages. First, Arabic language is written right to left. Second, it contains many letters that cannot be pronounced by most foreigners like ض ، غ ، ح ، خ، ظ. Moreover, Arabic language contains special characters called Diacritics which are special characters that help readers pronounced words correctly. For instance the statement السَّلامُ عَلَيْكُمْ وَرَحْمَةُ اللَّهِ وَبَرَكَاتُهُ containts special characters after most of the letters. The diactrics follow special rules to be given to a certain character. These rules are construct a complete area called النَّحْوُ الْعَرَبِيُّ. Compared to English, the Arabic language words letters are mostly connected اللغة as making them disconnected is difficult to read ا ل ل غ ة. ArbML helps fixing this by implementing many open-source projects that support Arabic, ML and NLP.

https://github.com/zaidalyafeai/ARBML

#machinelearning #deeplearning #artificialintelligence #nlp

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Forecasting at Uber: An Introduction
https://eng.uber.com/forecasting-introduction/

$1 million AAAI Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity!

https://lnkd.in/equKpQq

#HumanitarianAI

Microsoft ImageBERT | Cross-modal Pretraining with Large-scale Image-Text Data

https://syncedreview.com/2020/01/27/microsoft-imagebert-cross-modal-pretraining-with-large-scale-image-text-data/amp/

@ai_python_arXiv :
ArXiv Papers Related to Computer Science, AI, Deep Learning, Computer Vision, NLP, etc
From: @ai_python_en

Description

The Department of Computer Science at Smith College invites applications for two, two-year, benefits-eligible positions at the rank of Visiting Assistant Professor of Computer Science, to begin July 1, 2020.  The successful candidates will be prepared to teach five courses per year and must provide evidence of excellence in teaching and in research. The positions are open-field. The term of appointment for each position is for two years, ending June 2022. A Ph.D. in computer science or a closely related field is expected by the time of appointment. Candidates with the ability to work with diverse student populations are especially encouraged to apply.


Located in Northampton, MA, Smith College is the largest women’s college in the country and is dedicated to excellence in teaching and research across the liberal arts.  The faculty of outstanding scholars interact with students in small classes, as advisors, and through student-faculty research projects. Smith College offers opportunities to foster faculty success at every career stage, such as those listed here: https://www.smith.edu/about-smith/provost/faculty-development.  The College is a member of the Five College Consortium with Amherst, Hampshire and Mt. Holyoke Colleges, and the University of Massachusetts Amherst.  Students cross-enroll and faculty cross-teach across the Five Colleges. Details about the Department of Computer Science may be found at http://cs.smith.edu/ .


Diversity and a culture of equity and inclusion among students, staff, faculty, and administration are crucial to the mission and values of Smith College. We are an Affirmative Action/Equal Opportunity employer and do not discriminate on the basis of race, gender, age, color, religion, national origin, disability, sexual orientation, gender identity and expression or veteran status in the recruitment and employment of faculty and staff, and the operation of any of its programs and activities, as specified by all applicable laws and regulations. Women, historically underrepresented minorities, veterans, and individuals with disabilities are encouraged to apply.


Application Instructions

Submit application at http://apply.interfolio.com/73031 with a cover letter, curriculum vitae, a teaching statement, a research statement, and three confidential letters of recommendation. Review of applications will begin on March 1, 2020. 

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I’m the Inclusion Content Manager for Amazon Web Services (AWS) and I’ll looking for Canadian speakers in machine learning for our Ottawa Summit.

If you fit this criteria and are working for companies that are building on AWS, please reach out to me at diykhann@amazon.com.

Diya Khanna • diya.khanna@gmail.com

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