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Machine Learning 2021
ME Conferences cordially welcome all the participants all over the world to the "8th World Machine Learning and Deep learning Conference" which is going to be held at May 24, 2021, Webinar. The theme of the conference is “Intensify the world with Machine Learning”. Check out where the world is going with the recent advancements in the field of Machine Learning by grabbing this magnificent opportunity.
Come and explore the new technology of Artificial Intelligence from this gathering and inspire many young and innovative minds, practitioners, experts to learn the new ways to work and achieve through data. Your presence over the venue will add one more feather to the crown of Machine Learning 2021.
Take the step to submit your abstract at Machine learning 2021 conference. We welcome all type of research work related to Machine Learning. Find your interested topics from our conference highlights and prepare your research work with 300 words and confirm your presence at our conference.
Enroll your participation at Machine Learning 2021 conference. Confirm your slot by registering for the webinar. Confirm your slot by registering for the webinar. Early bird registration ends on or before February 28, 2021.
Why to attend?
Looking for a moment to learn something new and need a short break for professional life. Both are possible by attending the Machine Learning 2021 conference. Come and discover the beautiful places in Barcelona.
- Data Analyst
- Data Architect
- Cloud Architect
- Business Intelligence Developer
- President / Vice president
- Chairs / Directors
- Data Scientists
- Startup Professionals
- Scientists / Researchers
Deep learning is a subset of artificial intelligence which has the ability to do the work without human supervision. It is used in detecting objects, recognition of speech, translating the languages and making decisions. Deep learning is evolve with the digital era which is collected from every region in the world this data is termed as big data which is collected form the sources social media, internet, search engines, e- commerce platforms and online cinemas among others. Artificial Intelligence refers to the reflection of human intelligence in machines that are programmed to think like humans. It is a branch of computer science which emphasizes the development of intelligence machines who thinks and works like human.
Track 2: Robotic Process Automation (RPA)
Robotic process automation is a software robots running on virtual machine. With the use of robotic process automation the software users creates software robots and executes rule based business processes. They are mostly used in business operations. It permits representatives in an organization to design computer software or robotic methods to catch and interpret existing applications for handling an exchange, controlling information, setting off reactions and speaking with other advanced frameworks. They deliver enormous benefits like cost reduction, greater accuracy, delivery speed, solving problems, improving processes, conducting analysis which results in higher employee engagement and new revenue opportunities.
- Data migration
- Manufacturing & Retail
- Banking and financial services
Track 3: Virtual Reality (VR) and Gaming
Virtual reality uses the computer technology that is completely different from the real world. It is a computer generated simulation in which the user experiences an artificial three dimensional environment using electronic materials such a special googles with a screen fitted with sensors. VR gadgets utilized in the game business are empowered with interactive software and hardware. It is used for the entertainment purpose like video games and 3D cinema. Virtual reality is used in the applications of robotic methods, construction modelling and airplane simulation.
Track 4: Advancement of Cybersecurity
Artificial intelligence is the major contribution of advancement of cyber security. Cyber security refers to the technology that is designed to protect network, devices, programs, and data from unauthorized access. For effective cyber security needs a network security, application security, endpoint security, data security, identity management, cloud security, mobile security, disaster recovery etc., Machine learning is being used to identify the miscellaneous behaviour form hackers by modelling the network behaviour and improving the threat detection.
- Cyber security framework
- Privacy engineering
- Public safety communications security
- Medical organizations
- Smart grid
- Voting systems security
Artificial intelligence in healthcare is used to interpret the complicated medical and healthcare data by the utilization of machine learning algorithms and artificial intelligence. Machine learning is used in the field of radiology to detect and diagnose diseases through computerized tomography and magnetic resonance imaging. The identification of drug interactions in medical literature can be possible by improving the natural language processing. This electronic health record data helps to identify the symptoms of the patients.
- Diagnosis processes
- Treatment protocol development
- Drug development
- Personalized medicine
- Patient monitoring and care
Pattern recognition is the automated recognition of patterns by using machine learning. It is a technology that matches the information stored in the data base with the incoming data. It is mostly used in industries and businesses. It solves the problems of fake biometrics. Speech recognition also known as automatic speech recognition is the ability of the machine to identify the words spoken and convert them into the readable text. Some of the algorithms used in the detection of speech are Viterbi search, deep neural networks, discrimination training.
- Computer vision
- Finger print analysis
- Optical character recognition
- Image pattern recognition
- Sentiment analytics
- Big data analysis
Track 7: Voice Assistants
A voice assistant is a digital assistant that uses speech synthesis, voice recognition and language processing algorithms to provide relevant information requested by the user. They are integrated by into many devices such as cell phones, computers, and smart speakers. They can access the GPS location. The voice assistants are used in the fields of industries, healthcare, banking and marketing. The mass adoption of artificial intelligence in client’s regular day to day existences is additionally filling the move towards voice applications. The number of IoT gadgets, for example, smart thermostats, apparatuses, and speakers are giving voice aides greater utility in an associated client's life.
- Voice recognition
- Speech synthesis
- Natural language processing
- Customer support
Track 8: Email Spam and Malware Filtering
Spam email is an unwanted junk email sent out in bulk to an indiscriminate recipient list. It can also be a malicious attempt to gain access to your computer. Email spam comes in different types that are disguised marketing campaigns for business promotions. They can be promotion of job offers and weight loss programs. Malware filtering is the detection of viruses and spyware. If a malware is detected the message will be deleted. The notification will be sent to the senders if the message is not delivered or deleted.
- Commercial advertisements
- Antivirus warnings
- Email spoofing
- Sweepstakes winners
- Money scams
Track 9: Biometric Security Solutions
Biometric scanners are the biological measurements that can be used for the verification of the identity. It involves using data security software to automatically recognise people based on their behavioural characteristics. The use of biometric strengthens the security and improves convenience. It protects the sensitive documents and valuables. It stores each person unique biometric identity. Users don't have to recall passwords or PIN numbers and user’s accounts can't be shared. Even though the data is encrypted it is better to store the biometric data like Touch ID and Face ID than storing it with the service provider.
- Voice Recognition
- Fingerprint Scanning
- Facial Recognition
- Iris Recognition
- Heart-Rate Sensors
Track 10: Self-driving cars
Self-driving cars are the self- governing vehicle which is capable of sensing the environment and moves safely without the human input. They are combined of sensors like radar, sonar, GPS and many more. The self-driving cars has features of speed controlling and emergency breaking by driver assistance technology as they still require human driver control. Self-driving vehicles are equipped with different sorts of sensors and radars. Self-driving vehicles are being created with deep neural network, a sort of deep learning design with numerous computational stages, or levels, in which neurons are recreated from the climate that enact the organization.
- Transport systems
- Automobile industry
- Health care
Track 11: Object Detection with Digits
Object detection with digits is a bit of Deep Learning. It is a champion among the most troublesome issues in computer vision and is the underlying stage in a few computer vision applications. Due to its existence, Deep Learning Conferences consistently remember a track for Object Detection with Digits. The deep learning GPU training system (DIGITS) places the intensity of profound learning in the possession of information researchers and specialists. Utilizing DIGITS you can perform normal deep learning assignments, for example, overseeing information, characterizing networks, preparing a few models in equal, observing preparing execution progressively, and picking the best model from the outcomes program.
Track 12: Online Customer Support
Online Customer Service is characterized as any assistance that assists clients with taking care of issues. Such a help is generally associated with a business or brand which sells items and offers uphold. The trading of messages is generally done progressively and includes channels like live chat, call, email or social media. The online customer support provides a high level service of customer information analysis and reporting, teleservices, voice over and many more.
- Disposal of a product
Track 13: Big Data, Data Science and Data Mining
Big Data is a field that gets ways break down, systematically extract data from informational collections that are unpredictable to be managed by conventional information handling application programming. Big Data challenges including capturing data, data storage, data analytics, search, transfer, representation, questioning, and refreshing and information security.
Data science is a field that joins all that is identified with the cleansing, preparation and last examination of information. Data science solidifies the programming, intelligent reasoning, number-crunching, and insights. It gets information in the fastest manner and supports the restriction of looking at things with a substitute viewpoint.
Data mining is essentially the way toward collecting information from the databases. We can thus 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.
- Cost reduction
- Faster, Better decision making
- New Products and Services
Track 14: Online Fraud Detection
Fraud Detection with machine learning gets conceivable because of the capacity of ML algorithms which gains from recorded fraud designs and remembers them in future exchanges. Machine learning algorithms appear more effective than humans when it comes to the speed of information processing. Also, ML algorithms are able to find out the fraud traits that a human cannot detect. With the utilization of deep neural networks the artificial intelligence model architecture is inspired by the structure of biologic brains.
- Payment Fraud
- Identity theft
- Account takeover
- ID document forgery
- Fake account identification
Track 15: Virtual Reality and Augmented Reality
Virtual Reality is the use of computer technology to create an unreal environment in which the person interacts with an artificial three dimensional environment using electronic devices. Virtual reality is applied in the field of medicine, architecture, military, anatomy teaching, astronaut training and others. Augmented Reality is a combination of a real world and virtual world. The components used for virtual reality are processor, display, sensors and input devices. The augmented reality is applied in the field of archaeology, e- commerce and education. In healthcare the examples include x-ray based on tomography, detecting tumor.
- Marketing campaigns
- Product activations and launches
- Print advertising
Track 16: Internet of Things (IoT)
Internet of things refers to the devices around the world connected to the internet all collecting and sharing data. It is the convergence of technologies like machine learning, sensors, real time analytics and embedded system for the purpose of connecting and exchanging data with other devices and systems. It has the ability to access the information form anywhere, improves communication between connected devices, transferring data packets, reducing the need of human intervention. IoT devices are used to monitor blood pressure, heart rate monitors, pacemaker, hearing aids and electronic wristbands.
- Smart home
- Medical diagnosis and healthcare
- Energy management
- Environmental monitoring
Track 17: Deep Learning Frameworks
Deep Learning belongs to field of Machine Learning which deals with the building blocks for designing, training and validating deep neural networks. It depends on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex. It can be able to solve more complex problems and perform greater tasks. Deep Learning Framework is a basic supporting essential structure that assists with making the unpredictability of DL little easier.
Track 18: Computer Vision and Image Processing
Computer Vision is a sub-set of Artificial Intelligence .The main goal of artificial intelligence 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 which transforms the visual images into a description of the words. Image Processing is the field of enhancing the images by tuning many parameter and features of the images. So, Image Processing is the subset of Computer Vision.
- Rescaling image
- Correcting illumination
- Changing tones
- Object detection
- Face detection
- Hand writing recognition
Track 19: Predictive Analytics
Predictive Analytics is the branch of advanced analytics techniques from data mining, predictive modelling and machine learning which offers a clear view of the present and deeper insight into the future. It utilizes various procedures and calculations from statistics and data mining, to examine current and recorded data to predict the result of future events and interactions. In business, predictive models exploit designs found in historical and value-based information to recognize dangers and openings.
Track 20: Automated Machine Learning
Automated machine learning belongs to the field of data science which refers to the process of applying machine learning to real-world problems. It was proposed as an artificial intelligence based solution to the ever-growing challenge of applying machine learning. The high level of computerization in AutoML permits non-specialists to utilize AI models and procedures without requiring turning into a specialist in the field first. It makes business in every industry like healthcare, financial markets, marketing, sports, manufacturing and many others applications.
- Self-Driving Cars
- Fraud Detection
- Medical Diagnosis
Track 21: Computer Aided Medical Diagnostics
Computer aided diagnosis also called as computer aided detection are systems that help specialists in the translation of medical images. It is an interdisciplinary development joining segments of electronic devices and computer vision with radiological and pathology image processing. CAD is used in the diagnosis of breast cancer, lung cancer, coronary artery disease, congenital heart disease, Alzheimer disease, nuclear medicine.
Track 22: Automatic Machine Translation
Automatic machine translation is the software that translates text or speech form one language into target language. It belongs to the field computational linguistics. The human translation process may be described to be decoding and re- encoding. A deep learning based machine translation has made a progress in recent years. It can quickly translate web pages or sentences. Machine translation and computer aided translation software uses the previous data base, dictionaries to translated text.
- Google Translate
- Microsoft Translator
- Amazon Translate
- IBM Watson Language Translator
- Cloud Translation API
- Bing Translator
Scope and importance of Machine Learning:
Machine Learning as innovation breaks down enormous pieces of information, facilitating the undertakings of information researchers in a mechanized cycle and is picking up a ton of noticeable quality and acknowledgment. AI has changed the way information extraction and translation works by including programmed sets of conventional strategies that have supplanted customary factual methods. Information investigation has customarily been described by the experimentation approach – one that gets difficult to utilize when there are huge and heterogeneous informational collections being referred to. It is for this very explanation that enormous information was scrutinized for being overhyped.
Machine Learning Global Market:
The worldwide AI market totalled $1.4 billion of every 2017 and is assessed to reach $8.8 billion by 2022, developing at an accumulate yearly development rate (CAGR) of 43.6% for the time of 2017-2022. The machine learning programming incorporates answers for different applications and compatible stages for high-processing applications. In the services portion, the managed service segment is relied upon to develop at a higher CAGR, though proficient service segment is required to be a larger contributor during the forecast period. The managed service is supposed to be growing faster, as it causes associations to build productivity and saves cost for overseeing on-request AI administrations. The development of professional services is mostly represented by the complexity of operations and expanding deployment of machine learning solutions.
Artificial Intelligence: Applications and Global Markets:
The global market for artificial intelligence should grow from $3.5 billion in 2018 to reach $26.1 billion by 2023 at a compound annual growth rate (CAGR) of 49.1% for the period of 2018-2023. Based on technology, the global artificial intelligence market is segmented into machine learning, natural language processing, computer vision and expert systems. Based on deployment mode, the global artificial intelligence market is divided into on premise deployment and cloud deployment. Based on organization size, the artificial intelligence market is segmented into small and medium-sized enterprises and large enterprises.
Machine Learning companies:
- iTechArt Group
- DogTown Media
- Xicom Technologies