预告丨2018年值得关注的200场机器学习会议,爱可

日期:2019-10-09编辑作者:服务器

预告丨2018年值得关注的200场机器学习会议,200场

2017年马上就要过去了,这一年你的收获怎么样?在学习的过程中,独自学习与向别人学习同样重要,其中通过各种会议了解AI行业研究成果是个不错的提高自己的方法。对于专注于机器学习的伙伴来说,2018年有哪些值得关注的会议呢?以下内容来源于Alex Kistenev的总结,建议收藏!

 

按国家总计,这两百场会议中,有80场在美国举办,29场在英国举办,12场在加拿大举办,并且大部分会议在北美举办。

 

按城市总计,这两百场会议中,有28场在伦敦举办,20场在旧金山举办,10场在纽约举办。

 

以下大会列表按照举办时间列出。

 

一月

11–13 Jan, Data Science & Management of Data (CoDS-COMAD). Goa, India.

16–18 Jan, International Conference on Agents and Artificial Intelligence (ICAART). Funchal, Madeira, Portugal.

18 Jan, Alternative Data Conference. New York, USA.

17–19 Jan, Global Artificial Intelligence Conference. Santa Clara, USA.

17–19 Jan, AI NEXTCon. Seattle, USA.

18–19 Jan, AI in Healthcare Summit. Boston, USA.

19–21 Jan, International Conference on Control Engineering and Artificial Intelligence (CCEAI). Boracay, Philippines.

23 Jan, Women in Machine Intelligence Dinner. San Francisco, USA.

25 Jan, Beyond Machine’s Deep Learning Bootcamp. Berlin, Germany.

25–26 Jan, AI Assistant Summit San Francisco. San Francisco, USA.

25–26 Jan, Deep Learning Summit San Francisco. San Francisco, USA.

25–26 Jan, Artificial Intelligence & Machine Learning 101. Chicago, USA.

25–26 Jan, AI on a Social Mission Conference. Montreal, Canada.

27 Jan, Data Day Texas. Austin, USA.

27–30 Jan, Applied Machine Learning Days. Lausanne, Switzerland.

28–29 Jan, International conference on Computers, Data Management and Technology Applications (ICCDMTA). Cairo, Egypt.

30–31 Jan, The AI Congress London. London, UK.

31 Jan, Chatbot Summit. Tel Aviv, Israel.

31 Jan — 1 Feb, Age of AI. San Francisco, USA.

31 Jan — 3 Feb, rstudio::conf 2018. San Diego, USA.

 

二月

2–7 Feb, AAAI Conference. New Orleans, USA.

3–8 Feb, Developer Week. San Francisco, USA.

5–6 Feb, Artificial Intelligence Dev Conference at DeveloperWeek. Oakland, USA.

5–6 Feb, Conversational Interaction Conference. San Jose, USA.

5–7 Feb, Applied AI Summit. London, UK.

6–7 Feb, Predictive Analytics Innovation Summit. San Diego, USA.

6–8 Feb, Chief Data & Analytics Officer Winter. Miami, USA.

7–8 Feb, Big Data & Analytics Summit Canada. Toronto, Canada.

8 Feb, AI Evolution. New York, NY, USA.

8–9 Feb, DataScience Salon Miami. Miami, USA.

14–17 Feb, International Research Conference Robophilosophy. Vienna, Austria.

20 Feb, Women in AI Dinner London. London, UK.

22 Feb, Bottish. Online.

22 Feb, AI Inside Summit. Vienna, Austria.

26–28 Feb, International Conference on Machine Learning and Computing (ICMLC). Macau, China.

27 Feb, AI 4 Business. Lint, Belgium.

27–28 Feb, Gartner Data & Analytics Summit. Sydney, Australia.

 

三月

5–6 Mar, European Artificial Intelligence Innovation Summit. London, UK.

5–8 Mar,ACM/IEEE International Conference on Human Robot Interaction (HRI). Chicago, USA.

5–8 Mar, O’Reilly Strata Data Conference. San Jose, USA.

5–8 Mar, Gartner Data & Analytics Summit. Grapevine, USA.

7–8 Mar, Big Data & Analytics Innovation Summit. Singapore.

7–8 Mar, AI and Sentiment Analysis in Finance. Hong Kong.

7–11 Mar, ACM IUI. Tokyo, Japan.

8 Mar, The Conversational Interface Conference. London, UK

12–14 Mar, Winter Conference on Applications of Computer Vision (WACV). Lake Tahoe, USA.

13–14 Mar, Sentiment Analysis Bangalore 2018. Bangalore, India.

15–16 Mar, AI Assistant Summit London. London, UK.

15–16 Mar, Deep Learning in Retail & Advertising Summit London. London, UK.

15–16 Mar, Big Data & Analytics Innovation Summit. Melbourne, Australia.

15–16 Mar, Artificial Intelligence & Machine Learning 101. Boston, USA.

18–21 Mar, Shoptalk. Las Vegas, USA.

19–21 Mar, Gartner Data & Analytics Summit. London, UK.

19–22 Mar, IBM Think. Las Vegas, USA.

20 Mar, The AI Customer Summit. London, UK.

20–21 Mar, AI & Robotics: Compliance, Liability & Risk Management. San Francisco, USA.

20–22 Mar, Analytics and Data Summit. Redwood Shores, USA.

22 Mar, Data Innovation Summit. Stockholm, Sweden.

22 Mar, Innovation Summit 2018 America. Chicago, USA.

22 Mar, AI & Robotics Director’s Forum. London, UK.

23–25 Mar, Machine Learning Prague 2018. Prague, Czech Republic.

26–29 Mar, GPU Technology Conference. Silicon Valley, USA.

26–27 Mar, EmTech Digital 2018. San Francisco, USA.

29–31 Mar, International Conference on Advanced Computational Intelligence (ICACI). Xiamen, China.

 

四月

5–6 Apr,  Future of Information and Communication Conference (FICC). Singapore.

8–11 Apr, AnacondaCON 2018. Austin, TX, USA.

9–11 Apr,  International Conference on Artificial Intelligence and Statistics (AISTATS). Lanzarote, Canary Islands.

9–11 Apr, SpeechTEK. Washington, USA.

10–13 Apr, O’Reilly Artificial Intelligence Conference Beijing. Beijing, China

12 Apr, Applied Artificial Intelligence Conference. San Francisco, USA.

12 Apr, AI World Forum. San Francisco, USA.

15–20 Apr,  ICASSP 2018. Calgary, Canada.

16–17 Apr, Artificial Intelligence. Las Vegas, USA.

16–17 Apr, Automation and Robotics. Las Vegas, USA.

17–19 Apr, Monage. Mountain View, USA.

18–19 Apr, AI Expo Global. London, UK.

18–19 Apr, Big Data & Analytics Innovation Summit. Hong Kong.

19 Apr, AI Conference Moscow. Moscow, Russia.

19–20 Apr, Big Data Innovation Summit. San Francisco, USA.

22–27 Apr, Enterprise Data World (EDW). San Diego, USA.

23–25 Apr, RPA & AI Summit. Copenhagen, Denmark.

23–27 Apr, The Web Conference. Lyon, France.

24–28 Apr, IEEE International Conference on Soft Robotics (RoboSoft). Livorno, Italy.

25–27 Apr, European Symposium on Artificial Neural Networks. Bruges, Belgium.

26–27 Apr, Big Data & AI Leaders Summit. Sydney, Australia.

29 Apr — 2 May, O’Reilly Artificial Intelligence Conference New York. New York, USA.

30 Apr — 3 May,  International Conference on Learning Representations (ICLR). Vancouver, Canada.

30 Apr — 3 May, TalkRobot. New Orleans, USA.

 

五月

1–2 May, F8 — Facebook Developer Conference. San Diego, USA.

1–4 May, Accelerate AI: Open Data Science Conference East. Boston, USA

3–4 May, AI Congress Vegas. Las Vegas, USA.

3–4 May, The Data Science Conference. Chicago, USA.

3–5 May, SIAM International Conference on Data Mining (SDM18). San Diego, USA.

8 May, Prepare.ai Conference. St. Lous, USA.

9–10 May, Train AI. San Francisco, USA.

9–10 May, Machine Learning Innovation Summit. San Francisco, USA.

15–17 May, Business of Bots 2018. San Francisco, USA.

16–18 May, Colombian Conference on Applications in Computational Intelligence (ColCACI). Medellin, Columbia.

16–19 May, IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR). Brisbane, Australia.

17 May, Rise of AI Conference 2018. Berlin, Germany.

20–24 May, Data Disrupt. New York, USA.

21–25 May, The International Conference on Robotics and Automation (ICRA). Brisbane, Australia.

21–24 May, O’Reilly Strata Data Conference London. London, UK.

21–24 May, Chief Analytics Officer — Spring. San Francisco, USA.

22–23 May, Gartner Data & Analytics Summit. São Paulo, Brazil.

23–24 May, LDV Vision Summit. New York, USA.

24–25 May, Deep Learning Summit Boston. Boston, USA.

31 May — 1 Jun, dotAI. Paris, France.

 

六月

1–6 Jun, Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). New Orleans, USA.

3–6 Jun,  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Melbourne, Australia.

3–7 Jun, Predictive Analytics World Las Vegas. Las Vegas, USA.

4 Jun, Data Science Salon New York. New York, USA.

5–6 Jun, Gartner Data & Analytics Summit. Mumbai, India.

6–7 Jun, Machine Intelligence Summit Hong Kong. Hong Kong.

11–12 Jun, CogX London 2018: Festival of All Things AI. London, UK.

12–13 Jun, AI Toronto. Toronto, Canada.

12–13 Jun, Predictive analytics World Industry 4.0. Munich, Germany.

12–14 Jun, AI Summit London. London, UK.

14–15 Jun, AI & Machine Learning for Clinical Trial and R&D Advancements. Philadelphia, USA.

14–15 Jun, Gartner Data & Analytics Summit. Tokyo, Japan.

14–19 Jun, International Conference on Machine Learning and Data Mining (MLDM). New York, USA.

18–23 Jun, CVPR 2018. Salt Lake City, USA.

20–21 Jun, Conference on Big Data Analysis and Data Mining. Rome, Italy.

20–22 Jun, Distributed Computing and Artificial Intelligence (DCAI). Toledo, Spain.

24–29 Jun,  International Conference on Automated Planning and Scheduling (ICAPS). Delft, The Netherlands.

25–28 Jun, International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE). Montreal, Canada.

26–29 Jun, International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR). Delft, The Netherlands.

26–30 Jun, Robotics: Science and Systems (RSS). Pittsburgh, USA.

27–28 Jun, AI, Machine Learning and Sentiment Analysis Applied to Finance. London, UK.

28 Jun, AI for CxOs Dinner San Francisco. San Francisco, USA.

29 Jun, The 4th Research and Applied AI Summit. London, UK.

TBA Jun, ML Conference. Munich, Germany.

 

七月

1 Jul, AI+Talk at SVIEF. Santa Clara, USA.

5–8 Jul,  The Conference on Human Computation and Crowdsourcing (HCOMP). Zurich, Switzerland.

5–9 Jul, COLT 2018. Stockholm, Sweden.

8–12 Jul, Conference on Research and Development in Information Retrieval (SIGIR). Detroit, USA.

9–11 Jul, Applied AI Summit. London, UK.

10–11 Jul, Mobile Beat. San Francisco, USA.

10–12 Jul, Computing Conference. London, UK.

10–15 Jul, International Conference on Machine Learning (ICML). Stockholm, Sweden.

10–15 Jul, International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Stockholm, Sweden.

11–15 Jul,  Industrial Conference on Data Mining (ICDM). New York, USA.

13–19 Jul,  International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI). Stockholm, Sweden.

14–19 Jul,  International Conference on Machine Learning and Data Mining (MLDM). New York, USA.

15–20 Jul,  Annual Meeting of the Association for Computational Linguistics (ACL). Melbourne, Australia.

19–21 Jul, Multimedia & Artificial Intelligence. Rome, Italy.

23–24 Jul, International Conference on Data Mining (ICDM). Istanbul, Turkey.

31 Jul — 1 Aug, AI Summit Hong Kong. Hong Kong.

TBA Jul, Anthill Inside. Bangalore, India.

 

八月

12–16 Aug, SIGGRAPH 2018. Vancouver, Canada.

19–23 Aug,  KDD 2018. London, UK.

20–24 Aug,  IEEE International Conference on Automation Science and Engineering (CASE). Munich, Germany.

20–24 Aug, International Conference on Pattern Recognition (ICPR). Beijing, China.

20–25 Aug, International Conference on Computational Linguistics (COLING). Santa Fe, USA.

21–22 Aug, Artificial Intelligence, Robotics & IoT. Paris, France.

30–31 Aug, Computer science, Machine Learning and Big data analytics conference. Dubai, UAE.

 

九月

2–6 Sep,  Interspeech 2018. Hyderabad, India.

3–6 Sep,  British Machine Vision Conference (BMVC). Newcastle upon Tyne, UK.

4–7 Sep, O’Reilly Artificial Intelligence Conference San Francisco. San Francisco, USA.

6–7 Sep, Intelligent Systems Conference (IntelliSys). London, UK.

8–14 Sep, European Conference of Computer Vision (ECCV). Munich, Germany.

9–12 Sep, International Symposium Advances in Artificial Intelligence and Applications (AAIA). Poznan, Poland.

10–11 Sep, Robots and Deep Learning. Singapore.

11–12 Sep, Big Data Innovation Summit. Boston, USA.

11–14 Sep, O’Reilly Strata Data Conference New York. New York, USA.

17–18 Sep, International Conference on Human-Robot Interaction (ICHRI). Rome, Italy.

17–18 Sep, 2nd Artificial Intelligence Innovation Summit. San Francisco, USA.

18–20 Sept, International Joint Conference on Computational Intelligence (IJCCI). Seville, Spain.

18–20 Sep, AI Summit San Francisco. San Francisco, USA.

19–21 Sep, International Conference on Computer-Human Interaction Research and Applications (CHIRA). Seville, Spain.

20–21 Sep, Deep Learning in Healthcare Summit London. London, UK.

23–25 Sep, Auto AI. Berlin, Germany.

27–29 Sep, IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO). Genova, Italy.

 

十月

1–2 Oct, AI Expo Europe. Amsterdam, The Netherlands.

1–5 Oct, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain.

3–4 Oct, MACHINA Summit. London, UK.

5 Oct, BCS Machine Intelligence competition. London, UK.

8–11 Oct, O’Reilly Artificial Intelligence Conference London. London, UK.

10–11 Oct, World Summit AI. Amsterdam, The Netherlands.

15–17 Oct, Minds Mastering Machines [m3]. London, UK.

17–18 Oct, Nordic Data Science and Machine Learning Summit. Stockholm, Sweden.

17–18 Oct, Predictive Analytics World London. London, UK.

21–24 Oct, AI Deep Dive at Money 2020. Las Vegas, USA.

22–26 Oct, International Conference on Information and Knowledge Management (CKIM). Turin, Italy.

23 Oct, Women in AI Dinner Toronto. Toronto, Canada.

23–24 Oct, VB Summit. Berkeley, USA.

24–25 Oct, Predictive Analytics Innovation Summit. Chicago, USA.

25–26 Oct, Deep Learning Summit Toronto. Toronto, Canada.

31 Oct — 04 Nov, Open Data Science Conference West. San Francisco, USA.

 

十一月

1–2 Nov, Big Data & Analytics Innovation Summit. London, UK.

5–8 Nov, TalkRobot at Web Summit. Lisbon, Portugal.

13–14 Nov, Predictive Analytics World Berlin. Berlin, Germany.

13–15 Nov, AI Summit Cape Town. Cape Town, South Africa.

14–16 Nov, Big Data Spain. Madrid, Spain.

15–16 Nov, Future Technologies Conference 2018. Vancouver, Canada.

21–22 Nov, Big Data & Analytics Innovation Summit. Beijing, China.

28–29 Nov, AI Expo North America. Santa Clara, USA.

29–30 Nov, AI Expo North America. Santa Clara, USA.

TBA Nov, AI & Robotics Main Event. London, UK.

 

十二月

3–8 Dec, NIPS. Montréal, Canada.

7 Dec, Machine Learning Innovation Summit. Dublin, Ireland.

VLDB
http://vldb2016.persistent.com/important_dates.html
March, September 5-9
ICDE
October, May 16
SIGMOD
Nov, June 26
SIGKDD
Feb 12, May 12, June 10
CIKM
May, Oct
ECML-PKDD
Jan 4, Apr 4, (J Mar 30), Sep 19
WWW
Oct, Feb, Apr
AAAI
Sep, Feb
TKDD
Dec, Jun

The following is chronological listing of links to articles that have been published. To view my woefully neglected blog, visit zacklipton.wordpress.com.

取有法,舍有道,坚持必有收获
AI - 人工智能;CV - 机器视觉;DL - 深度学习;DM - 数据挖掘;DS - 数据科学;DV - 数据可视化;IOT - 物联网;ML - 机器学习;NLP - 自然语言处理

TKDE
SIAM
Mar
PAKDD
Jan 15, April 19
KR
Nov, Apr
KSEM
Jun, Oct
SEKE
Mar 1, July1
KES-SDM
Nov, Apr
(J)
DKE
澳门金莎娱乐网站,April 23
DMKD
Feb 29, Jul 11
http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=49447©ownerid=49896
IJKM

Does Deep Learning Come from the Devil? (Distilling the Debate from Yandex Machine Learning Conference) (Oct. 9, 2015)
KDnuggets
Recycling Deep Learning Models with Transfer Learning (Aug. 14, 2015)
KDnuggets
arXiv.org and the 24 Hour Research Cycle (July 21, 2015)
KDnuggets
Deep Learning and the Triumph of Empiricism (July 7, 2015)
KDnuggets
Not So Fast: Questioning Deep Learning IQ Results (June 15, 2015)
KDnuggets
A Rigorous and Readable Review on Recurrent Neural Networks (June 2, 2015)
Terminal Blog
Looking Back at "Finding Structure in Time" (May 22, 2015)
Terminal Blog
Demystifying Long Short Term Memory (LSTM) Recurrent Neural Networks (May 18, 2015)
Terminal Blog
Will the Real Data Scientists Please Stand Up? (May 18, 2015)
KDnuggets
On Cloud Machine Startups, Ostrich Mania, and The Uncanny Valley (May 14, 2015)
KDnuggets
No More Local Minima? (May 4, 2015)
Terminal Blog
The Myth of Model Interpretability (April 27, 2015)
KDnuggets
Cloud Machine Learning: Comparing Amazon, IBM Watson & Microsoft Azure ML (April 15, 2015)
KDnuggets
Idiot-Proof Validation (April 8, 2015)
Terminal Blog
Learning to Read with Recurrent Neural Networks (April 5, 2015)
Terminal Blog
Gold Mine or Blind Alley? Functional Programming for Big Data and Machine Learning (April 1, 2015)
KDnuggets
Do We Need More Training Data or More Complex Models? (March 23, 2015)
KDnuggets
The Economics of Virtualization (March 10, 2015)
Terminal Blog
Failing Optimally – Data Science’s Measurement Problem (March 4, 2015)
KDnuggets
Data Science's Most Used, Confused, and Abused Jargon (Feb. 10, 2015)
KDnuggets
(Deep Learning's Deep Flaws)'s Deep Flaws (Jan. 26, 2015)
KDnuggets
The High Cost of Maintaining Machine Learning Systems (Jan. 21, 2015)
KDnuggets
MetaMind Competes with IBM Watson Analytics and Microsoft Azure Machine Learning (Jan. 14, 2015)
KDnuggets
Differential Privacy: How to make Privacy and Data Mining Compatible (Jan. 9, 2015)
KDnuggets
Stanford’s AI100: Century-Long Study on Effects of Artificial Intelligence on Human Life (Dec. 26, 2014)
KDnuggets
IBM Watson Analytics vs. Microsoft Azure Machine Learning (Part 1) (Dec. 16, 2014)
KDnuggets
Geoff Hinton AMA: Neural Networks, the Brain, and Machine Learning (Dec. 9, 2014)
KDnuggets

  • [AI]Facebook Messenger will start making suggestions for you based on your conversations
  • [AI]Facebook Messenger’s AI “M” suggests features to use based on your convos
  • [AI]Facebook’s AI assistant will now offer suggestions inside Messenger
  • [AI]Google Details Tensor Chip Powers
  • [AI]OpenAI Just Beat Google DeepMind at Atari With an Algorithm From the 80s
  • [AI]Soon, Your Car May Be Able to Read Your Expressions
  • [AI]Tappest to Exhibit @MooseFS at @CloudExpo New York | #SDN #AI #Storage - All The Internet Of Things
  • [AI]What is Driving the Shift Towards Cloud-Based CFD and FEA Simulation?
  • [DL]"How #AI can make business more human #fintech #machinelearning #deeplearning #bigdata #Insurtech #ML #DL #tech https
  • [DL]11 Great Hadoop, Spark and Map-Reduce Articles
  • [DL]4 Ways to Revolutionize Customer Experience With AI
  • [DL]A conversation with AI pioneer Yoshua Bengio – MilTech
  • [DL]A Peek at Trends in Machine Learning – Andrej Karpathy – Medium
  • [DL]Allen Cell Explorer: A portal to the human cell
  • [DL]brianspiering/awesome-dl4nlp
  • [DL]Dr. GP Pulipaka on Twitter
  • [DL]eyes gaze warping 2
  • [DL]Global Bigdata Conference
  • [DL]Google's dedicated TensorFlow processor, or TPU, crushes Intel, Nvidia in inference workloads - ExtremeTech
  • [DL]How Artificial Intelligence Is Reshaping ECommerce
  • [DL]How do I become a data scientist? – Monica Rogati – Medium
  • [DL]IBM to power cloud deep learning with latest Nvidia graphics chip - SiliconANGLE
  • [DL]Intel Collaborating with Preferred Networks in Japan on Deep Learning | Intel Newsroom
  • [DL]Machine learning predicts the look of stem cells
  • [DL]Medical Image Analysis with Deep Learning — II – Taposh Dutta-Roy – Medium
  • [DL]More Extreme in Every Way: The New Titan Is Here - NVIDIA TITAN Xp | The Official NVIDIA Blog
  • [DL]Open sourcing Sonnet - a new library for constructing neural networks | DeepMind
  • [DL]Recurrent neural networks and other machines that learn algorithms
  • [DL]Some Lesser Known Machine Learning Libraries - ParallelDots
  • [DL]Stanford researchers use new algorithms for drug development
  • [DL]The Deep Learning Saga
  • [DL]The Good, Bad & Ugly of TensorFlow
  • [DL]Top KDnuggets tweets, Mar 29 – Apr 04: Free Must-Read Books for #MachineLearning; #Apache Slug, new #BigData project
  • [DL]Video Friday: Pepper's Fish Mode, Deep Learning in the Warehouse, and Stealing From a Delivery Robot
  • [DL]Why Artificial Intelligence is Here to Stay
  • [DS]Big Data & Data Analytics Market in Homeland Security and Public Safety: 2017-2022 – satPRnews
  • [DS]Customer Analytics Innovation Summit Chicago
  • [DS]HDInsight—Hadoop, Spark, and R Solutions for the Cloud | Microsoft Azure
  • [DS]Strata London Community Lightning Talks - Strata Data Conference in London 2017
  • [DV]A selling solution that automates quoting process within a span of 10 minutes – satPRnews
  • [DV]Bay Area d3 User Group
  • [DV]Chess Outcomes vs Total Moves [OC] • r/dataisbeautiful
  • [DV]Cost Breakdown for a US Domestic Flight [OC] • r/dataisbeautiful
  • [DV]Flag Rods Market Poised to Expand at a Robust Pace – satPRnews
  • [DV]How Do We Know That? – Video of My Talk at UW
  • [DV]Interactive visualization is still alive
  • [DV]US Video Game Publisher Revenue from 2011 to 2016 • r/dataisbeautiful
  • [IoT]Flash-Based Array Market Will Reach US$ 63 Million by 2024 – satPRnews
  • [IoT]Global IoT Sensors Market By Type, By Application Industry Analysis, Trends and Forecast 2015 - 2023 - All The Internet Of Things
  • [IoT]International Provider of Security Services Engages BeWhere to Provide Asset Management Solutions
  • [IoT]Operational Predictive Maintenance Market to Rise at 23.2% CAGR by 2024 – satPRnews
  • [IoT]Orchestration Middleware Market Will Reach US$ 15.29 Bn by 2024 – satPRnews
  • [IoT]Robots: Lots of features, not much security - All The Internet Of Things
  • [IoT]The Dangers of the Internet of Things or IoT - All The Internet Of Things
  • [ML][1704.01926] Semantically-Guided Video Object Segmentation
  • [ML][R] Federated Learning: Collaborative Machine Learning without Centralized Training Data • r/MachineLearning
  • [ML]A Statistical Guide to the “Impossible”
  • [ML]Adobe Thinks It Can Make Your Selfies a Lot Less Ugly With This Mystery App
  • [ML]AI in Healthcare Summit, San Francisco, June 26-27 – KDnuggets Offer
  • [ML]AI Won’t Change Companies Without Great UX
  • [ML]Analytics and the cloud: NoSQL databases
  • [ML]Automatic visualization is a bad idea, generally speaking
  • [ML]avoiding investigation loops and their traps
  • [ML]Baidu AI achieves 'zero shot learning' ability using natural language - ExtremeTech
  • [ML]BioPandas
  • [ML]Cloud, Watson, & Blockchain: Amalgam Insights’ View of IBM Interconnect
  • [ML]Cloudera Government Forum
  • [ML]Consumers confused about artificial intelligence: Study - ET CIO
  • [ML]Data Scientist – Device Insights at Samsung in Mountain View, California | AnalyticTalent.com
  • [ML]Datasets of the Week, March 2017
  • [ML]Dataworks Summit München 2017 – day two
  • [ML]dlsys-course/assignment1
  • [ML]Facebook's AI assistant now stalks you on Messenger to suggest features - SiliconANGLE
  • [ML]Factoring Massive Numbers: Machine Learning Approach
  • [ML]Federated Learning: Collaborative Machine Learning without Centralized Training Data
  • [ML]For today: Zaloni and the Data Lake. Are Machine Learning and Artificial Intelligence Destined to Rule The World!?
  • [ML]Get Ready to Take on 2017's Analytics Infrastructure Challenges - DZone Big Data
  • [ML]Global Clinical Decision Support Systems Market to Incur Rapid Extension by 2020 – satPRnews
  • [ML]How Synthetic Data Can Overcome Privacy Concerns - DZone Big Data
  • [ML]How To Use Artificial Intelligence To Stay On Top Of Your Bottom Line | Articles | Big Data
  • [ML]Inspiring Fifty: Netherlands 2017 - Inspiring fifty
  • [ML]intel/torch: Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
  • [ML]Jupyter Notebook Viewer
  • [ML]Machine Learning Quick Start – Don't Fear the Machines - Data Tech Blog
  • [ML]Machines learning evolves, and hackers stand to gain -- GCN
  • [ML]Microsoft Maluuba teaches management 101 to machines in its first paper since being acquired
  • [ML]Now available: open source Microsoft Cognitive Toolkit | Microsoft + Open Source
  • [ML]Robot Check
  • [ML]Robot security guards start rolling out because of lack of human guards
  • [ML]Speeding up workloads: OpenPOWER takes aim at analytics and cognitive computing - SiliconANGLE
  • [ML]Thursday News: IoT, AI, Machine Learning, Dataviz, Spark, Data Engineering, Courses
  • [ML]Uber’s open source data visualization tool now goes beyond maps
  • [ML]Use dual axes with care, if at all
  • [ML]Using Machine Learning as a Data Storytelling Engine - insideBIGDATA
  • [ML]Using Machine Learning at The Pensions Regulator
  • [NLP]What to Make of PwC’s New Report on Job-Stealing Robots?

本文由澳门金莎娱乐网站发布于服务器,转载请注明出处:预告丨2018年值得关注的200场机器学习会议,爱可

关键词:

磁盘管理澳门金莎娱乐网站,磁盘管理命令应用

101道RHCE考题和详细答案(九),101道rhce考题答案 创建分区相关命令: 4.1 df 命令 1)df 查看磁盘使用情况      ...

详细>>

Linux查看物理CPU个数,物理封装

Linux查看物理CPU个数、核数、逻辑CPU个数,linux个数 一、概念 1、物理CPU 插槽上的CPU个数, 物理cpu数量,可以数不重...

详细>>

2013年线务员理论知识复习题带答案,线路维护员

通信线路的知识,通信线路知识 01.全色谱全塑市内电缆结构,其芯线为什么要纽绞?        (p1面)电缆结构:芯...

详细>>

访问控制器的栈校验机制,ViewPager控件的使用

使用Rserve远程执行R脚本,rserver脚本 注1:关于Rserve网上有很多资料可以参考,详细情况可以参考博客下面的“参考资...

详细>>