Vijayan K Asari
Professor University of Dayton USA
Panos M. Pardalos
Distinguished Professor of Industrial and Systems Engineering University of Florida USA
Faculty of Engineering and Environment Northumbria University UK
Full Professor University of Twente Netherlands
Principle Software Developer Oracle USA
Professor University of Greenwich UK
Mary Mehrnoosh Eshaghian-Wilner
Professor of Engineering Practice USC University of southern california USA
Professor China University of Mining and Technology China
Recommended Global EEE & Engineering Conferences
Machine Learning 2018
MEConferences team cordially invites all participants across the world to attend the 5th World Machine Learning and Deep Learning Congress (Machine Learning 2018) which is going to be held during August 30-31 in Dubai, UAE. The main theme of the conference is “Machine Learning: Discovering the New Era of Intelligence". This conference aimed to expand its coverage in the areas of Machine Learning and Deep Learning where expert talks, young researcher’s presentations will be placed in every session of the meeting will be inspired and keep up your enthusiasm. We feel our expert Organizing Committee is our major asset, however Speakers are what make events stand out. World Machine Learning and Deep Learning Congress is bringing the most innovative minds, practitioners, experts and thinkers to inspire and present to the delegates new innovative ways to work and innovate through their data. Your presence over the venue will add one more feather to the crown of Machine Learning 2018.
Machine Learning is a method of teaching computers how to perform complex tasks that cannot be easily described or processed by humans and to make predictions. It is a combination of Mathematical Optimization and Statics. In the other hand, Deep Learning is the subset of ML that focus even more narrowly like neuron level to solve any problem. Machine Learning 2018 is comprised of the following sessions with 20 tracks designed to offer comprehensive sessions that address current applications, discoveries and issues of Machine Learning and Deep Learning.
Target audience for the conference:
- Data Engineers/Developers
- Startup Professionals
- President/Vice president
And last but not the least……….
- Anyone interested in Machine Learning & thrives to make the future developed and better
Sessions / Tracks
MEConferences team cordially invites all the participants from all over the world to attend World Machine Learning and Deep Learning Congress during August 30 - 31, 2018 in Dubai, UAE. This includes prompt keynote presentations, Oral talks, Poster presentations and Exhibitions.
Track: Machine Learning
Machine Learning is a subset of Artificial Intelligence (AI) that provides computers with the ability to learn without being explicitly programmed and to make intelligent decisions. It also enables machines to grow and improve with experiences. It has various applications in science, engineering, finance, healthcare and medicine.
Advantages of Machine Learning-
- Useful where large-scale data is available
- Large-scale deployments of Machine Learning beneficial in terms of improved speed and accuracy
- Understands non-linearity in the data and generates a function mapping input to output (Supervised Learning)
- Recommended for solving classification and regression problems
- Ensures better profiling of customers to understand their needs
- Helps serve customers better and reduce attrition
And many more………
This Machine Learning Conference is focused on adding more value & knowledge to the revolutionary era of Intelligence.
Track: Deep Learning
Deep Learning is a subset of Machine Learning which deals with deep neural networks. It is based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations. Machine Learning Conferences has added the topic Deep Learning Conferences which will clear the doubts & will add more knowledge from the most innovative minds through out the globe.
Track: Artificial Intelligence
Artificial Intelligence is a technique which enables computers to mimic human behaviour. In other words, it is the area of computer science that emphasizes the creation of intelligent machines that work and reacts like humans. With increasing world of AI, knowledge transfer is also very much necessary. For that Machine Learning Conferences has added this very important topic of Artificial Intelligence meetup.
Types of Artificial Intelligence:
- Narrow Artificial Intelligence - Narrow artificial intelligence is also known as weak AI. It is an artificial intelligence that mainly focuses on one narrow task. Narrow AI is defined in contrast to either strong AI or artificial general intelligence. All currently existing systems consider artificial intelligence of any sort is weak AI at most. It is commonly used in sales predictions, weather forecasts & playing games. Computer vision & Natural Language Processing (NLP) is also a part of narrow AI. Google translation engine is a good example of narrow Artificial Intelligence
- Artificial General Intelligence
- Artificial Super Intelligence
Track: Internet of Things (IoT)
The Internet of things (IoT) refers to an umbrella that covers the entire network of physical devices, home appliances, vehicles and other items embedded with software, sensors, actuators, electronics and connectivity, or we can say with an IP address (Internet Protocol), which enables these objects to connect and exchange data, which resulting in enhanced efficiency, accuracy and economic advantage in addition to reduced human involvement.
A human brain has neurons that help in adaptability, learning ability & to solve any problem. Unlike Human brain, computer scientists dreamt for computers to solve the perceptual problems that fast. And hence, ANN model came into existence. Artificial Neural Networks is nothing but a biologically inspired computational model that consists of processing elements (neurons) and connections between them, as well as of training and recall algorithms. Artificial Neural Networks (ANN) Conference will help to build relation with the most eminent persons in the field.
Track: Deep Learning Frameworks
Deep Learning is a subset of Machine Learning which deals with deep neural networks. It is based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations. Deep Learning is able to solve more complex problems and perform greater tasks. Deep Learning Framework is an essential supporting fundamental structure that helps to make complexity of DL little bit easier.
Machine learning works effectively in the presence of huge data. Medical science is yielding large amount of data daily from research and development (R&D), physicians and clinics, patients, caregivers etc. These data can be used for synchronizing the information and using it to improve healthcare infrastructure and treatments. This has potential to help so many people, to save lives and money. As per a research, big data and machine learning in pharma and medicine could generate a value of up to $100B annually, based on better decision-making, optimized innovation, improved efficiency of research/clinical trials, and new tool creation for physicians, consumers, insurers and regulators. Due to the presence of enormous data in Healthcare, Machine Learning Conferences are adding medical Science topic in their every meetup.
Natural Language Processing (NLP) is a sub-set of artificial intelligence that focuses on system development that allows computers to communicate with people using everyday language. Natural language generation system converts information from computer database into readable human language and vice versa.
The field of NLP is divided in 2 categories:-
- Natural Language Understanding (NLU)
- Natural Language Generation (NLG)
Computer Vision is a sub-branch of Artificial Intelligence whose goal is to give computers the powerful facility for understanding their surrounding by seeing the things more than hearing or feeling, just like humans. It is used for processing, analyzing and understanding digital images to extract information from that. In other words, it transforms the visual images into description of the words. Machine Learning Conference gives a platform for the researchers to come & talk on a common platform.
Track: Pattern Recognition
Pattern Recognition is a classification of Machine Discovering that predominantly concentrates on the acknowledgement of the structure and regularities in detail; however, it is considered almost similar to machine learning. Pattern Recognition has its cause from engineering, and the term is known with regards to Computer vision. Pattern Recognition, for the most part, has a better enthusiasm to formalize, illuminate and picture the pattern and give the last outcome, while machine learning customarily concentrates on expanding the recognition rates before giving the last yield. Pattern Recognition algorithms normally mean to give a reasonable response to every single input and to perform in all probability coordinating of the data sources, taking into charge their statistical variety. There are various uses of Pattern Recognition.
The use of machines in the public has expanded widely in the most recent decades. These days, machines are utilized as a part of a wide range of businesses. As their introduction with people increment, the communication additionally needs to wind up smoother and more characteristic. Keeping in mind the end goal to accomplish this, machines must be given an ability that let them get it the encompassing condition. Exceptionally, the intentions of a person. At the point when machines are eluded, this term includes to computers and robots. Deep Learning conference will talk in depth about facial expression & emotion detection.
Track: Predictive Analytics
Predictive Analytics is the branch of advanced analytics which offers a clear view of the present and deeper insight into the future. It uses different techniques and algorithms from statistics and data mining, to analyze current and historical data to predict the outcome of future events and interactions. Big Data Conference, Artificial Intelligence Conference as well as Machine Learning summit keep Predictive Analytics as its main part because of its vast scope.
Track: Big Data, Data Science and Data Mining
Nowadays, a huge quantity of data is being produced daily. Machine Learning uses those data and provides a noticeable output that can add value to the organization and will help to increase ROI,
Big Data is informational indexes that are so voluminous and complex that conventional data handling application programming is lacking to manage them. Big Data challenges incorporate capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, and updating and data security. There are three dimensions to Big Data known as Volume, Variety and Velocity.
Data Science manages both structured and unstructured data. It is a field that incorporates everything that is related to the purging, readiness and last investigation of data. Data science consolidates the programming, coherent thinking, arithmetic and statistics. It catches information in the keenest ways and supports the capacity of taking a gander at things with an alternate point of view.
Data mining is essentially the way toward collecting information from gigantic databases that was already immeasurable and obscure and after that utilizing that information to settle on applicable business choices. To put it all the more essential, Data mining is an arrangement of different techniques that are utilized as a part of the procedure of learning disclosure for recognizing the connections and examples that were beforehand obscure. We can thusly term data mining as a juncture of different fields like artificial intelligence, data room virtual base management, pattern recognition, visualization of data, machine learning, and statistical studies and so on.
Track: Big Data Analytics
Big Data Analytics gives a handful of usable data after examining hidden patterns, correlations and other insights from a large amount of data. That as a result, leads to smarter business moves, higher profits, more efficient operations and finally happy customers. And Big Data Conference adds more value to it.
Big Data Analytics adds value to the organization in following ways:
- Cost reduction
- Faster, Better decision making
- New Products and Services
Track: Dimensionality Reduction
In Machine Learning, when machine captures data, they find random data. Then machine learning uses dimensionality reduction or dimension reduction is the process for reducing the number of random variables under consideration by obtaining a set of principal variables. It can be divided into feature selection and feature extraction.
Track: Model Selection and Boosting
Model Selection is the undertaking of choosing a statistical model from an arrangement of candidate models, given information. In the least difficult cases, a prior arrangement of information is considered. However, the assignment can likewise include the outline of trials with the end goal that the information gathered is appropriate to the problem of model selection. Given candidate models of comparable prescient or illustrative power, the least complex model is well on the way to be the best decision
Boosting is a machine learning ensemble meta-algorithm for essentially lessening inclination, and furthermore changes in supervised learning, and a group of machine learning algorithms which change over weak learners to strong ones. A weak learner is characterized to be a classifier which is just marginally related to the genuine characterization (it can name cases superior to anything irregular speculating). Conversely, a strong learner is a classifier that is subjectively all around connected with the genuine classification. It plays a very important role in Machine Learning Conference.
Track: Object Detection with Digits
Object detection with digits is a piece of Deep Learning. It is a standout amongst the most difficult issues in computer vision and is the initial phase in a several computer vision applications. The objective of an object detection system is to recognize all examples of objects of a known classification in a picture. Because of its important existence, Deep Learning Conferences always include a track on Object Detection with Digits.
Track: Cloud Computing
Cloud Computing is a delivery model of computing services over the internet. It enables real-time development, deployment and delivery of broad range of products, services and solutions. It is built around a series of hardware and software that can be remotely accessed through any web browser. Generally, documents and programming are shared and dealt with by numerous clients and all information is remotely brought together as opposed to being put away on clients' hard drives. Machine Learning Conferences has included a special talk on Clod Computing.
Robotic Automation lets organizations automate current tasks as if a real person was doing them across applications and systems. RPA is a cost cutter and a quality accelerator. Therefore RPA will directly impact OPEX and customer experience, and benefit to the whole organization and this is why it becomes a main topic to be discussed in Machine Learning Conference.
World Machine Learning and Deep Learning Congress welcome presenters, exhibitors and attendees to Dubai, UAE during August 30-31, 2018. The organizing committee is preparing for an exciting and informative conference program including lectures, workshops, symposia on a wide variety of topics, poster presentations and various programs for participants from across the world. We invite you to join us at the Machine Learning 2018, where you will be sure to have a meaningful experience with scholars from around the globe. All members of the Machine Learning 2018 organizing committee look forward to meeting you in Dubai, UAE.
Scope and importance:
Previously Machine Learning & Deep Learning was used to construct software from training examples. Its method was also extended to support data mining and knowledge discoveries. Then ML & DL started doing perceptual tasks like deep learning for computer vision, speech recognition etc. After that its main work was automated decision making & anomaly detection (Cyber Security, Fraud Detection and Machine Diagnosis). But the Future of ML & DL is beyond imagination and it can control & work on variety of topics like:
- Detecting and Correcting for Bias
- Risk Sensitive Optimization
- Explanations of Black Box Systems
- Verification and Validation
- Integrating ML Components into Larger Software Systems
The market of Machine Learning & Deep Learning is growing exponentially worldwide. According to the research, the global machine learning market is expected to grow from $ 1.41 Billion in 2017 to $ 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% and the Global Machine Learning as Service market is expected to grow from $ 480.94 million in 2015 to reach $ 5,394.87 million by 2022 with a CAGR of 41.2%.
Machine learning enabled solutions are being significantly adopted by organizations worldwide to enhance customer experience, Return on Investment (ROI), and to gain a competitive edge in business operations. Moreover, in the coming years, applications of machine learning in various industry verticals are expected to rise exponentially. Some of the verticals are:
o Applications of machine learning in BFSI
- Fraud and Risk Management
- Investment Prediction
- Sales and Marketing Campaign Management
- Customer Segmentation
- Digital Assistance
- Others (compliance management and credit underwriting)
- Healthcare and Life Sciences
o Applications of machine learning in healthcare and life sciences
- Disease Identification and Diagnosis
- Image Analytics
- Drug Discovery/Manufacturing
- Personalized Treatment
- Others (clinical trial research and epidemic outbreak prediction)
o Applications of machine learning in retail
- Inventory Planning
- Upsell and Cross Channel Marketing
- Segmentation and Targeting
- Recommendation engines
- Others (customer ROI and lifetime value, and customization management)
o Applications of machine learning in telecommunication
- Customer Analytics
- Network Optimization
- Network Security
- Others (digital assistance/contact centres analytics and marketing campaign analytics)
- Government and Defence
o Applications of machine learning in government and defence
- Threat Intelligence
- Autonomous Defence system
- Others (sustainability and operational analytics)
o Applications of machine learning in manufacturing
- Predictive Maintenance
- Demand Forecasting
- Revenue Estimation
- Supply Chain Management
- Others (root cause analysis and telematics)
- Energy and Utilities
o Applications of machine learning in energy and utilities
- Power/Energy Usage Analytics
- Seismic Data Processing
- Smart Grid Management
- Carbon Emission
- Others (customer specific pricing and renewable energy management)
- Others (Education, Agriculture, Media and Entertainment, and Education)
Why Dubai, UAE:
UAE is the city of world’s best architecture and now it is stepping towards the advanced future of Artificial Intelligence. UAE believes in Smart Smarter Smartest… and therefore the government took AI adoption one step further by installing a minister in-charge of AI.
Few actions of UAE Government in the field of AI and Machine Learning in past years are:
- 2000 – E-Government-the first government to move to e-government system
- 2013 – Smart Government-launched services to public wherever they are round the clock
- 2015 – Smart Transformation – Achieved 100% e-government transformation
- 2017 – Artificial Intelligence-launched AI strategy as part of UAE Centennial 2071
Why to Attend???
ML conference gathers communities to discuss the recent research and application of Algorithms, Tools, and Platforms to solve the hard problems that exist within organizing and analyzing massive and noisy data sets. Machine Learning 2018 invites attendees from around the world focused on learning about ML & DL. This would be one of best opportunity to reach the largest assemblage of participants from the ML community. Conduct demonstrations, distribute information, meet with current and potential customers, make a splash with a new product line, and receive name recognition at this 2-day event. World’s renowned speakers, the most recent techniques, highlights, discoveries and the newest updates in ML & DL fields are hallmarks of this conference.
- Extraordinary speakers
Discover advances in ML and DL algorithms and methods from the world's leading speakers, researchers and scholars. Learn from industry experts in speech & pattern recognition, neural networks, image analysis and NLP. Explore how Machine Learning and Deep Learning will impact finance, healthcare, manufacturing, search & transportation.
- Discover emerging trends
The congress will showcase the opportunities of advancing trends in Machine Learning & Deep Learning and their impact along with successful applications in business. It will also focus on the challenges and areas of improvement related to the field of research and applications. Learn the latest technological advancements & industry trends from a global line-up of experts.
- Expand your network
A unique opportunity to connect with industry leaders, influential technologists, Machine Learning Professionals & founders leading the deep learning revolution. Learn from & interact with various industry innovators sharing best practices to advance the smart artificial intelligence revolution and become a part of it.
Industries Associated with Machine Learning:
- GOOGLE – For developing a photographic memory
- IBM – For embedding Watson where it’s needed most
- BAIDU – For accelerating mobile search with artificial intelligence
- SOUNDHOUND – For giving digital services the power of human speech
- ZEBRA MEDICAL VISION – For using deep learning to predict and prevent diseases
- PRISMA - For making masterpieces out of snapshots
- IRIS AI - For speeding up scientific research by surfacing relevant data
- PINTEREST - For serving up a universe of relevant pins to each and every user
- TRADEMARKVISION - For helping start-ups make their mark without any legal confusion
- DESCARTES LABS - For preventing food shortages by predicting crop yields
Universities Associated with Machine Learning:
- Carnegie Mellon University
- University of Michigan Ann Arbor
- Columbia University
- University of Washington
- Georgia Tech
- University of California San Diego
- University of Massachusetts Amherst
- John Hopkins University
- University of Illinois Urbana Champaign
- Penn State University
- University of North Carolina Chapel Hill
- California Institute of Technology
- University of Wisconsin Madison
Major Societies & Groups Worldwide-
- The International Machine Learning Society (IMLS)
- American Statistical Association
- IEEE Computer Society
- European Knowledge Discovery Network of Excellence (KDNet)
- National Centre for Data Mining (NCDM)
- Pacific Rim International Conferences on Artificial Intelligence
- Canadian Artificial Intelligence Association
- The European Coordinating Committee on AI (ECCAI)
- Special Interest Group on Artificial Intelligence, Computer Society of India
- Japanese Society of Artificial Intelligence
- Sociedad Mexicana de Inteligencia Artificial
- Russian Association for Artificial Intelligence
- Computing Research Association
- The Society for the Study of Artificial Intelligence AND Simulation of Behaviour
- The International Neural Network Society
USA: ML Society; The International Machine Learning Society; The Association For The Advancement Of Artificial Intelligence; The Artificial Intelligence Society; AI & Society; The Association for Uncertainty in Artificial Intelligence; Society for Artificial Intelligence; Conference on Uncertainty in Artificial Intelligence; Artificial Intelligence International; Slovenian Pattern Recognition Society; International Association of Computer Science and Information Technology; Global Cleantech Cluster Association; Czechoslovak Pattern Recognition Society; Bulgarian Association for Pattern Recognition; The Swiss Association for Pattern Recognition; The British Machine Vision Association and Society for Pattern Recognition;
Europe: European Association for Artificial Intelligence; Conexus Deep Learning Society; Deep Learning Society – Atlantic Rim Collaboratory; the Hellenic Artificial Intelligence Society; the European Coordinating Committee for Artificial Intelligence; Artificial Intelligence International; The Association for Uncertainty in Artificial Intelligence; Special Interest Group of the Brazilian Computer Society; French Association for Pattern Recognition and Interpretation; National Committee of the Russian Academy of Sciences for Pattern Recognition and Image Analysis; Mexican Association for Computer Vision, Neurocomputing and Robotics, Nederlandse Vereniging voor Patroonherkenning en Beeldverwerking; Italian Association for Pattern Recognition
Asia Pacific & Middle East: Indian Unit for Pattern Recognition and Artificial Intelligence; Artificial Intelligence Society of Hong Kong; Pattern Recognition and Machine Intelligence Committee of the Chinese Association of Automation; Artificial Intelligence Association of India; The Society for the Study of Artificial Intelligence and Simulation of Behaviour; Australian Pattern Recognition Society; Hong Kong Society for Multimedia and Image Computing; Pattern Recognition and Machine Intelligence Committee of the Chinese Association of Automation; The Macau Society for Pattern Recognition and Image Processing; Pakistani Pattern Recognition Society (PRRS); Computer Vision and Pattern Recognition Group of The Korean Institute of Information Scientists and Engineers
- 6th Convention on Robots and Deep Learning, September 10-11, 2018, Singapore
- 16th Deep Learning Summit, January 25-26, 2018, San Francisco
- Deep Learning Summit, September 20-21, 2018, London
- Artificial Intelligence Conference, January 17-19, 2018, Santa Clara, CA, USA
- Deep Learning for Enterprise Summit, January 25-26, 2018, San Francisco, CA, USA
- AI Assistant Summit, January 25-26, 2018, San Francisco, USA
- Deep Learning in Finance Summit, March 15-16, 2018, London, UK
- Deep Learning in Retail and Advertising Summit, March 15-16, 2018, London, UK
- The AI Conference Beijing (O'Reilly), April 10-13, 2018, Beijing, China
- Machine Intelligence Summit, April 12-13, 2018, Hong Kong
- Deep Learning Summit, April 12-13, 2018, Hong Kong
- Deep Learning in Healthcare Summit, May 24-25, 2018, Boston, USA
- AI in Industrial Automation Summit, June 21-22, 2018, San Francisco, USA
- Deep Learning for Robotics Summit, June 21-22, 2018, San Francisco, USA
- 14th Conference on Machine Learning and Data Mining, July 14-19, 2018, New York, USA
- Applied AI Summit, July 9-11, 2018, London, UK
- Congress on Computer science, Machine Learning and Big data analytics August 30-31, 2018, Dubai UAE
- Summit on Artificial Intelligence and Neural Network, October 15-16, 2018, Helsinki, Finland
- 7th Conference on Artificial Neural Networks, October 05-07, 2018 Rhodes, Greece
- 5th conference on Artificial Intelligence, April 16-17, 2018, Las Vegas; USA
- Conference on Artificial Intelligence, Robotics & IoT, August 21-22, 2018, Paris, France
- Joint Conference on Neural Networks, July 08-13, 2018, Rio de Janeiro, Brazil
- Conference on Artificial Neural Networks, November 21-23, 2018, Kuala Lumpur, Malaysia
- 27th Conference on Artificial Neural Networks, October 05-07, 2018, Rhodes, Greece
- 4th Summit and Expo on Multimedia & Artificial Intelligence, July 19-21, 2018, Rome, Italy
What will you learn???
Knowledge is everywhere; you can learn whatever you want from any source. But Machine Learning 2018 has made your search easy & compiled 19 sessions on emerging topics at a single place. Those sessions are:
- Machine Learning
- Deep Learning
- Artificial Intelligence
- Artificial Neural Networks (ANN) & Chainer
- Deep Learning Frameworks
- The role of AI & Machine Learning in Medical Science
- Natural Language Processing (NLP) and Speech Recognition
- Computer Vision and Image Processing
- Pattern Recognition
- Facial Expression and Emotion Detection
- Predictive Analytics
- Big Data, Data Science and Data Mining
- Big Data Analytics
- Dimensionality Reduction
- Model Selection and Boosting
- Object Detection with Digits
- Cloud Computing
- Robotic Process Automation (RPA)
We feel our expert Organizing Committee is our major asset, however, Speakers are what make events stand out. World Machine Learning and Deep Learning Congress is bringing most innovative minds, practitioners, experts, thinkers, eminent Researchers, Scientists, Professors, Developers, Analysts and Newbies under a solitary rooftop to inspire and present to the delegates new innovative ways to work and innovate through their data. Your presence over the venue will add one more feather to the crown of Machine Learning 2018.
Types of Datasets in Machine Learning
Training Data Set:
Testing Data Set:
Past Conference Report
Automation and Robotics 2017 Report
Thanks to all our wonderful speakers, conference attendees, Automation and Robotics-2016 Conference was the best!
The 2nd World Congress on Automation and Robotics, hosted by the MEConferences was held during June 13-15, 2016 at DoubleTree by Hilton Philadelphia Airport, Philadelphia, USA with the theme “Automation and Robotics for a Sustainable Future". Benevolent response and active participation was received from the Editorial Board Members of OMICS Group Journals as well as from the scientists, engineers, researchers, students and leaders from the fields of Automation and Robotics, who made this event successful.
The meeting was carried out through various sessions, in which the discussions were held on the following major scientific tracks:
- Industrial Automation
- Automation Tools and Technologies
- Control and Mechatronic Systems
- Robotics and Applications
- Manufacturing Automation
- Internet of Things
- Process and Energy Automation
- Security in Manufacturing Industries
- Automation systems
- Automation solutions
The conference was initiated with a series of lectures delivered by both Honorable Guestsand members of the Keynote forum. The list included:
Eduard Babulak, The Institute of Technology and Business in Ceske Budejovice, Czech Republic
Farrokh Janabi Sharifi, Ryerson University, Canada
Petter Falkman, Chalmers University of Technology Sweden
James P Gunderson, GunderFish LLC, USA
Asim ur Rehman Khan, National University of Computer & Emerging Sciences, Pakistan
Jerry Vinther, Lillebaelt Academy University of Applied Sciences, Denmark
MEConferences offers its heartfelt appreciation to the Organizing Committee Members, adepts of field, various outside experts, company representatives and other eminent personalities who supported the conference by facilitating the discussion forums. MEConferences also took privilege to felicitate the Organizing Committee Members and Editorial Board Members who supported this event.
MEConferences is proud to announce the "5th World Machine Learning & Deep Learning Congress" to be held during August 30-31, 2018 Dubai, UAE.
For More details visit: https://machinelearning.conferenceseries.com/
All accepted abstracts will be published in respective Conference Series LLC LTD International Journals.
Abstracts will be provided with Digital Object Identifier by