Twenty things I wish I’d known when I started my PhD

Recommened By Jeff Dean and Russ Poldrack

#Paper

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Nasdaq Financial Framework to Build Ledger Agnostic Blockchain With Microsoft Azure

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New NLP News:

ML on code, Understanding RNNs, Deep Latent Variable Models, Writing Code for NLP Research, Quo vadis, NLP?, Democratizing AI, ML Cheatsheets, Spinning Up in Deep RL, Papers with Code, Unsupervised MT, Multilingual BERT

#NLP #ML #DL #Training #RNN #RL

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✅ Free Book Online

Artificial Intelligence in Business Gets Real

By S. Ransbotham, P. Gerbert, M. Reeves, D. Kiron, and M. Spira

#book

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Twisted: Event-driven networking engine written in Python

https://www.twistedmatrix.com
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Top 15 Python Libraries for Data Science
link

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Finding Similar Quora Questions with Word2Vec and Xgboost
link
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Recurrent Neural Networks by Example in Python:
Using a Recurrent Neural Network to Write Patent Abstracts
link

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Predicting Professional Players’ Chess Moves with Deep Learning
link

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❌ Online Book

Reinforcement Learning: An Introduction

🌎 Link Review

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NVIDIA CEO Jensen Huang addresses 700+ attendees of SC18, where he revealed the rapid adoption of the NVIDIA T4 cloud GPU.

🌎 Link Review

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Improving Neural Networks Hyperparameter Tuning, Regularization, and More

❌ Link Review

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Andrew Ng launches ‘AI for Everyone,’ a new Coursera program aimed at business professionals.

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The latest The machine learning Daily!

#paper

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Stop Installing Tensorflow Using pip for Performance Sake!

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🗒 A novel image encryption algorithm based on polynomial combination of chaotic maps and dynamic function generation
🗣 Meysam Asgari-Chenaghlu, Mohammad-Ali Balafar, Mohammad-Reza Feizi-Derakhshi

https://www.sciencedirect.com/science/article/pii/S0165168418303700

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✅ Problem Solving with Algorithms and Data Structures using Python

#Book

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Using GANs to generate Master[Finger]Prints that unlock 22-78% phones sensors (dep. on security level of sensor)
https://arxiv.org/pdf/1705.07386.pdf
doesn't get much more "adversarial" than that.

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Ph.D. position in deep learning for signal processing at University of Oldenburg

The Computational Audition Group at the Department of Medical Physics and
Acoustics, University of Oldenburg, Germany, seeks a highly motivated

PhD student
(75 % of full time, TV-L E13, 3 years, with possibility of extension)
in the field of Deep Learning for Signal Processing

Our group investigates audio signal recognition with multi-channel microphone
arrays, identifying important sound sources in real-world acoustic scenes, and
performing source separation to enhance e.g. an attended speech signal.

Applicants for the position must hold an academic university degree (master or
equivalent) in physics, engineering, computer science or a related discipline
and should have knowledge in at least one of the following fields:

- machine learning,
- speech recognition,
- acoustic event detection,
- speech and audio processing.

Excellent knowledge of scientific programming languages such as Python or
MATLAB, as well as excellent English language skills are required.

The position is funded by the newly established DFG collaborative research
centre CRC 1330 "Hearing Acoustics", which aims at improving human communication
in real-world acoustic scenes and is a long-term collaboration of researchers
from Oldenburg, Aachen and Munich. For more information about the CRC see
https://www.uni-oldenburg.de/sfb1330.

The Computational Audition Group is part of the Department of Medical Physics
and Acoustics at University of Oldenburg. We offer an international scientific
environment and world-class research facilities. For more information about the
group and the department see https://uol.de/computational-audition/ and
https://uol.de.de/en/mediphysics-acoustics/.

The University of Oldenburg is dedicated to increase the percentage of women in
science. Therefore, female candidates are strongly encouraged to apply. In
accordance to § 21 Section 3 NHG, female candidates with equal qualifications
will be preferentially considered. Applicants with disabilities will be given
preference in case of equal qualification.

Applications including a CV, a motivation letter, copies of relevant
certificates and the name and contact details of two references should be sent
as single pdf-file to joern.anemueller@uni-oldenburg.de or to

Dr. Jörn Anemüller
Faculty VI
Department of Medical Physics and Acoustics
Universität Oldenburg
D - 26111 Oldenburg
Tel. (+49) 441 798 3610

The application deadline is 28th of November 2018.

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