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Previous Speakers

Shabir Momin

Shabir Momin

ZengaTV Singapore

Anu Kukar

Anu Kukar

KPMG Australia

Tilila El Moujahid

Tilila El Moujahid

Microsoft United Arab Emirates

Erwin E. Sniedzins

Erwin E. Sniedzins

Mount Knowledge Inc. Canada

Samir El-Masri

Samir El-Masri

Digitalization.Cloud United Arab Emirates

Sylvester Juwe

Sylvester Juwe

British Gas UK

Harshavardhana Kikkeri

Harshavardhana Kikkeri

Kaaya Tech Inc USA

Jayatu Sen Chaudhury

Jayatu Sen Chaudhury

American Express India

Machine Learning 2019

About Conference


MEConferences team cordially invites all participants across the world to attend the 6th World Machine Learning and Deep Learning Congress (Machine Learning 2019) which is going to be held during October 14-15, 2019 Helsinki, Finland. The main theme of the conference is “Making world a new place with technology". This conference aimed to expand its coverage in the areas of Artificial Intelligence, Machine Learning and Deep Learning where expert talks, young researcher’s presentations will be placed in every session of the meeting will be inspired to keep up your enthusiasm. We feel our expert Organizing Committee is our major asset, however, speakers are what make events stand out. 6th 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 2019.

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. On the other hand, Deep Learning is the subset of ML that focus even more narrowly like a 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.

 

Who attends?

  • CIOs / GCIOs
  • CTOs / CDOs
  • President / Vice president
  • Chairs / Directors
  • Data Scientists / Developers
  • Startup Professionals
  • Scientists / Researchers
  • Professors

Industry Verticals:

  • Banking
  • Financial Services
  • Insurance
  • Telecommunications
  • Media
  • Transport
  • Healthcare
  • Pharmaceuticals
  • eCommerce & Retail
  • Oil & Gas
  • Energy
  • Infrastructure

And last but not the least……….

  • Anyone interested in Artificial Intelligence, Machine Learning & Deep Learning and thrives to make the future developed and better

Sessions / Tracks

Track: Artificial Intelligence

Artificial Intelligence is a technique which enables computers to mimic human behavior. 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.

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 the 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: 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 & 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 of Deep Learning Conferences which will clear the doubts & will add more knowledge from the most innovative minds throughout the globe.

 

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 the complexity of DL little bit easier.

 

Track: AI & Machine Learning in HealthCare & Medical Science

Machine learning works effectively in the presence of huge data. Medical science is yielding a 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 the 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.

 

Track: Artificial Neural Networks (ANN)

A human brain has neurons that help in adaptability, learning ability & to solve any problem. Unlike the Human brain, computer scientists dreamt for computers to solve the perceptual problems that fast. And hence, the 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 relationships with the most eminent persons in the field.

 

Track: Natural Language Processing (NLP) and Speech Recognition

Natural Language Processing (NLP) is a subset 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 into 2 categories:-

•           Natural Language Understanding (NLU)
•           Natural Language Generation (NLG)

 

Track: Pattern Recognition

Pattern Recognition is a classification of Machine Discovering that predominantly concentrates on the acknowledgment 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.

 

Track: Facial Expression and Emotion Detection

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 computers and robots. Deep Learning conference will talk in depth about facial expression & emotion detection.

 

Track: Computer Vision and Image Processing

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 a description of the words. Machine Learning Conference gives a platform for the researchers to come & talk on a common platform.

 

Track: Robotic Process Automation (RPA)

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 the main topic to be discussed in Machine Learning Conference.

 

Track: Virtual Reality and Augmented Reality

Virtual Reality is the technology for the presentation of complicated information, manipulations, and interactions of the person with them by the computer. It is a computer generated an interactive three-dimensional environment to simulate reality. It can show 3D and attach sounds and touch information increases extraordinarily data comprehensibility. It has entered the public awareness as a medical toy with equipment “Helmet-glove”, which was preferentially determined for a wide public.

Augmented Reality is a combination of a real scene viewed by a user and a virtual scene generated by a computer that augments the scene with additional information. It enhances the real life by superimposing virtual images and adds graphics, sounds & smell to the real world, as it exists. The user maintains a sense of presence in the real world, He/she can interact with the real world and is not cut off from the real world. Augmented Reality is most suitable for marketing campaigns, product activations and launches, print advertising and much more. It is also been used on the smartphones.

 

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 results in enhanced efficiency, accuracy and economic advantage in addition to reduced human involvement.

 

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 the following ways:

•           Cost reduction
•           Faster, Better decision making
•           New Products and Services

 

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: Cloud Computing

Cloud Computing is a delivery model of computing services over the internet. It enables real-time development, deployment and delivery of a 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 cloud computing.

Past Conference Report

Machine Learning 2018

In the presence of Business Professionals, Academicians, Practitioners, and Students involved in the development of high-quality education in all aspects of technical skills, Conference Series 5th World Machine Learning and Deep Learning Congress was held during August 30-31, 2018 in Dubai, UAE.

ME Conferences Group played host to a diverse panel of key members of the Machine Learning 2018 community from research lab, industry, academia, and financial investment practices, discussing the future of Artificial Intelligence, Machine Learning, Deep Learning, Big Data and RPA. This event was really aimed for examining where the technology is going in the future and purpose of the event was to provide an opportunity for cross-fertilization and development of ideas, in this field.

Focusing on Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things (IoT), The role of AI & Machine Learning in Medical Science, Robotic Process Automation (RPA), Artificial Neural Networks (ANN) & Chainer, Natural Language Processing (NLP) and Speech Recognition, Computer Vision and Image Processing, Pattern Recognition, Deep Learning Frameworks, Dimensionality Reduction, Model Selection and Boosting, Big Data, Data Science and Data Mining, Object Detection with Digits, Facial Expression and Emotion Detection, Cloud Computing, Predictive Analytics, Big Data Analytics, the two days of discussions enabled professionals to gain an insight into the current innovations and opened up networking opportunities.

Machine Learning 2018 Organizing Committee would like to thank the Moderators of the conference – Rohit Agarwal, Mobisy Technologies Pvt Ltd, India; Tanya Dixit, Qualcomm, India who contributed a lot for the smooth functioning of this event.

The conference was embarked with an opening ceremony followed by Keynote sessions and followed by series of lectures delivered by Honourable Guests and members of the Keynote forum.

The highlights of the meeting were the eponymous lectures, delivered by:

  •        Shabir Momin, ZengaTV, Singapore
  •        Anu Kukar, KPMG, Australia
  •        Tanya Dixit, Qualcomm, India
  •        Tilila El Moujahid, Microsoft, UAE
  •        Jayatu Sen Chaudhury, American Express, India
  •        Sriharsha Allenki, Qualcomm, India
  •        Niladri Shekhar Dutta, Ericsson, UAE
  •        Manoj Mishra, Union Insurance, UAE
  •        Eman AbuKhousa, UAE University, UAE
  •        Najati Ali-Hasan, Anchor IT Consultation, UAE
  •        Abbas M Al-Bakry, University of Information Technology and Communications, Iraq
  •        Rohit Agarwal, Mobisy Technologies Pvt Ltd, India
  •        Erwin E. Sniedzins, Mount Knowledge Inc., Canada
  •        Samir El-Masri, Digitalization.Cloud, UAE
  •        Sylvester Juwe, British Gas, United Kingdom
  •        Harshavardhana Kikkeri, Kaaya Tech Inc, USA
  •        Santosh Godbole, SSN Solutions Limited, India
  •        Ahmed AlMaqabi, Almaqabi, Kingdom of Bahrain
  •        Gaurav Pawar, Mobisy Technologies Pvt Ltd, India
  •        Kai Khalid Miethig, Tariq Faqeeh Engineering, Bahrain
  •        Abed Benaichouche, Inception Institute of Artificial Intelligence, Abu Dhabi, UAE

These talks were of great interest to the general technology and were enormously informative.

There were several poster presentations as well at the conference. The best poster award won by Mr. Rohit Agarwal & Mr. Gaurav Pawar for the title “An overview of deep learning based object detection techniques in retail domain” and Dr. Nabil Belgasmi for the title “Multiobjective deep reinforcement learning approach for ATM cash replenishment planning”.

5th World Machine Learning and Deep Learning Congress was a great success with the support of international, multi-professional steering committee and coordinated by the Journal of Computer Science & Systems Biology; Advances in Robotics & Automation; Journal of Proteomics & Bioinformatics. We are happy to announce our 6th World Machine Learning and Deep Learning Congress, which will be held during October 14-15, 2019 in Helsinki, Finland.


Past Reports  Gallery  

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Conference Date October 14-15, 2019

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