Human Activity Recognition Python
This is a web-application, where user register with username and image. Our contributions concern (i) automatic collection of realistic samples of human actions from movies based on movie scripts; (ii) automatic learning and recognition of complex action classes using space-time interest points and a multi-channel SVM. This tutorial aims at illustrating the capabilities of machine learning for estimating occupancy and human activities, using Scientific Python. Speech Recognition MY Final Year Project - Free download as PDF File (. This website is intended to host a variety of resources and pointers to information about Deep Learning. The data set has 10,299 rows and 561 columns. Speaker recognition is the process of automatically recognizing who is speaking by using the speaker-specific information included in speech waves to verify identities being claimed by people accessing systems; that is, it enables access control of various services by voice (Furui, 1991, 1997, 2000).  A Database for Fine Grained Activity Detection of Cooking Activities, M. The red line needs to be either entered manually or detected using a line detector. Two new modalities are introduced for action recognition: warp flow and RGB diff. Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. In the ilhouette based method, the recognition can be made by s. Human Activity Recognition Codes and Scripts Downloads Free. of the 11th Mediterranean Conf. We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. The activity recognition problem can therefore be formulated as a problem of multidimensional time series segmentation. Today we explore over 20 emotion recognition APIs and SDKs that can be used in projects to interpret a user’s mood. Successful research has so far focused on recognizing simple human activities. edu Chenying Zhang [email protected]
In addition, signi cant progress towards object categorization from images has been made in the recent years . The dataset includes around 25K images containing over 40K people with annotated body joints. Figure 1: The big picture of the entire area 2. Video Analysis to Detect Suspicious Activity Based on Deep Learning Learn how to build on AI system that can classify a video into three classes: criminal or violent activity, potentially. This repository provides the codes and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art", where we implement and evaluate several state-of-the-art approaches, ranging from handcrafted-based methods to convolutional neural networks. How? Remember that face recognition passes through several way stations, each contributing to the complete picture. Human activity recognition is an important area of computer vision research and applications. Uri Drory’s Activity. "Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks. Many machine learning courses use this data for teaching purposes. to detect human voice activity. Kot† † School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Latest News, Info and Tutorials on Artificial Intelligence, Machine Learning, Deep Learning, Big Data and what it means for Humanity. By now, you would have noticed several features of Facebook- ‘People You May Know’ and ‘Face Recognition’. The system can recognise user-defined laser gestures throw a camera. Provide details and share your research! But avoid …. Username and Passwords. How to use the speech module to use speech recognition and text-to-speech in Windows XP or Vista. From the above result, it’s clear that the train and test split was proper. The system can recognise user-defined laser gestures throw a camera. The basketball players were equipped with jerseys with embedded accelerometer sensor. Cutting-edge AI software that protects national and business interests. 9% of emotion recognition rate in Beckman Institute for Advanced Science and Technology database. Human activity understanding encompasses activity recognition and activity pattern discovery. The reason for its importance is the abundance of applications that can benefit from such a technology. If students are using the Python interpreter for this activity, they need to know that exponents are entered using a double multiplication symbol, ‘**’. The project tasks shall be carried out individually. HRM Case studies plays vital role in management education specially in subjects like Human Resource Management (HRM), Personnel Management, PAAP etc. Students will need to break down the task into small simple steps. For our test, we used several photographs taken with regular camera phones. An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression D. Would you like to get an excellent and additionally low-cost pasttime? An effective craft is certainly amusing, pleasing all of which raise your life. The Human Activities with Smartphone Dataset is a multi-class classification situation where we are trying to predict one of the six possible outcomes. The coding exercises in this course use the Python programming language. The Python team Back row: Graham Chapman, Eric Idle, Terry Gilliam. In the following, the activity recognition model used in mHealthApp is. System-theoretic approaches to recognition of human actions model feature variations with dynamical systems and hence speciﬁcally consider the dynamics of the activity. (College of Human Ecology), director of community. affine6p 1. Amazon offers recommendations to policymakers on the use of facial recognition technology and calls for regulation of its use. Nowadays mobile phones become part of human life and it will change life style patterns. There are several techniques proposed in the literature for HAR using machine learning (see  ) The performance (accuracy) of such methods largely depends on good feature extraction methods. This activity focuses on students recognizing patterns in scientific notation. pdf), Text File (. Though arguably reductive, many facial expression detection tools lump human emotion into 7 main categories: Joy. OPPORTUNITY Activity Recognition Data Set Download: Data Folder, Data Set Description. Send comments to wsr nih. i need voice recognition code to identify human gender using. In each lecture, we describe a component's purpose and general structure. In vision-based activity recognition, a great deal of work has been done. search round the internet to get the persons profile. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Question PROJECT 2 2018-2019 Exercise Consider an Exotic option on a non-dividend-paying stock where the initial stock price is S 0 = $42, the risk-free rate is 4% per a. L-System Compiler and Renderer in Python. This is an excellent educational list, but there is something intrinsically & philosophically sad about the title “10 Human Attributes Found In Animals” because it already starts off on the wrong foot (or paw or fin or whatever). We will explain in detail how to use a pre-trained Caffe model that won the COCO keypoints challenge in 2016 in your own application. Practice Exercise: Predict Human Activity Recognition (HAR) The objective of this practice exercise is to predict current human activity based on phisiological activity measurements from 53 different features based in the HAR dataset. While there are many databases in use currently, the choice of an appropriate database to be used should be made based on the task given (aging, expressions,. Each gesture is assigned to a specific action. Human Activity Recognition : Comments, suggestions or submissions of the web links about neural networks with python code ©2016 - 2019. Face Expression Recognition and Analysis: The State of the Art Vinay Bettadapura College of Computing, Georgia Institute of Technology [email protected]
If students are using the Python interpreter for this activity, they need to know that exponents are entered using a double multiplication symbol, ‘**’. ) with associated durations. Scientists, teachers, writers, illustrators, and translators are all important to the program. As most of the available action recognition data sets are not realistic and are staged by actors, UCF101 aims to encourage further research into action recognition by learning and exploring new realistic action categories. Nowadays mobile phones become part of human life and it will change life style patterns. Real time face recognition. The task of determining the activity a subject is performing at a speci c time by using sensor data is called Human Activity Recognition (HAR). Amazon is selling facial recognition technology to U. Overview relevant related work. Please try again later. By now, you would have noticed several features of Facebook- ‘People You May Know’ and ‘Face Recognition’. I have the data in a sliding windows format, the length of each window is 256. edu Shutong Zhang [email protected]
In this study, we focus on detecting humans and do not consider recognition of their complex activities. Human Activity Recognition. On 28 September 2013 28 October 2017 By mashimo In data science, and one of them is a “Human Activity Recognition (HAR). Movements are often normal indoor activities such as standing, sitting, jumping, and going up stairs. Local, instructor-led live Python training courses demonstrate through hands-on practice various aspects of the Python programming language. Developing and understanding Automatic Speech Recognition (ASR) systems is an inter-disciplinary activity, taking expertise in linguistics, computer science, mathematics, and electrical engineering. Flexible Data Ingestion. We ended finding large datasets on a Stanford course's website-- Convolutional Neural Networks for Visual Recognition (CS 231n). Recognize People The Way You Want. The Windows Runtime API enables you to integrate your app with Cortana and make use of Cortana’s voice commands, speech recognition, and speech synthesis (text-to-speech, or TTS). Data Provider Deep Learning Model YAML Configuration file Insights on Learned Features Weight Decay and Momentum Neural networks that use convolution in place of general matrix multiplication HCF - hand-crafted features (Anguita et al. Search the world's most comprehensive index of full-text books. Open Position: Human Activity Analysis in the Operating Room from Multi-view Videos. The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Expertise in Machine Learning (PYTHON), ETL Tools, Data Visualization, Data Mining, Deep Learning, Information Retrieval Big Data and Data Warehousing. I was working on speech recognition elevator using arduino and speech recognition module v3, how can i interface these things ? I have only two weeks for defence so pleas help me ?. Global Architecture of an Activity Recognition Platform. DeepDive is a trained system that uses machine learning to cope with various forms of noise. edu, [email protected]
In each lab, the student creates a functioning block of the system. Pedestrian Detection OpenCV - PyImageSearch Seriously. Python package providing a set of tools for creating annotated images and illustrations. Learn about the basics of computer vision and object detection in Python. “walking”, “sitting”, “standing” etc. The method consists of two passes of denoising followed by a voice activity. E Software! if u like it please comment. It won't be perfect, but it will be able to run on a Pi and still deliver good results. eating, commuting, etc. More information can be found in the documentation. The goal of this work is to recognize realistic human actions in unconstrained videos such as in feature films, sitcoms, or news segments. Speech Recognition MY Final Year Project - Free download as PDF File (. When using this dataset, we request that you cite this paper. Password requirements: 6 to 30 characters long; ASCII characters only (characters found on a standard US keyboard); must contain at least 4 different symbols;. The coding exercises in this course use the Python programming language. It is well-known that biometrics are a powerful tool for reliable automated person identification . Search the world's most comprehensive index of full-text books. 3D Convolutional Neural Networks for Human Action Recognition by Ji et al. Additional resources, about rpy2 in particular or demonstrations of polyglot data analysis using rpy2 to call R from Python, are available (don't hesitate to notify us about other resource, but avoid Python vs R trolls unless funny):. Despite the increasing power of modern computers, human observers (even children) remain vastly superior to the best computer vision algorithms at quickly and accurately identifying objects in the visual scene. The project tasks shall be carried out individually. DeepDive-based systems are used by users without machine learning expertise in a number of domains from paleobiology to genomics to human trafficking; see our showcase for examples. Expertise in Machine Learning (PYTHON), ETL Tools, Data Visualization, Data Mining, Deep Learning, Information Retrieval Big Data and Data Warehousing. eating, commuting, etc. Home Courses Human Activity Recognition using smartphones Variables and data types in Python. To train the random forest classifier we are going to use the below random_forest_classifier function. Comparing to traditional methods such as using accelerometers or gyroscopes for activity recognition, acoustic-based methods can collect rich information of human activities together with the activity context, and therefore are more suitable for recognizing high-level compound. Sheheryar Arshad, Chunhai Feng, Yonghe Liu, Yupeng Hu, Ruiyun Yu, Siwang Zhou, Heng Li. Free printable worksheets and activities for preschool, kindergarten and grade school learning. Mobile phone technology is an active area of research and now at. This represents 8% of the proceedings (total=472 papers). Face detection and recognition using maximum likelihood classifiers on Gabor graphs. In this study, we focus on detecting humans and do not consider recognition of their complex activities. There’lso are in truth many subconscious benefits of developing hobbies. "walking", "sitting", "standing" etc. Ankit Dixit is a deep learning expert at AIRA Matrix in Mumbai, India and having an experience of 7 years in the field of computer vision and machine learning. Wi-Chase: A WiFi based Human Activity Recognition System for Sensorless Environments. To recognize the face in a frame, first you need to detect whether the face is present in the frame. RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. You will see updates in your activity send me the matlab code for automatic speech recognition. Please try again later. “ Sergio is a leading expert on computer vision and pattern recognition. Image Classification problems are ones in which images must be algorithmically assigned a label from a discrete set of categories. Asking for help, clarification, or responding to other answers. Practice Exercise: Predict Human Activity Recognition (HAR) The objective of this practice exercise is to predict current human activity based on phisiological activity measurements from 53 different features based in the HAR dataset. Download Face Recognition System for free. The method consists of two passes of denoising followed by a voice activity. IEEE WoWMoM 2017. m File You can see the Type = predict(md1,Z); so obviously TYPE is the variable you have to look for obtaining the confusion matrix among the 8 class. This means that the addition of facial recognition function could be added to live webcam streams, web crawlers, or other formats where images or videos containing faces are displayed digitally. A strong interest in applying computational methods to human-computer interaction, for example intelligent user interfaces, is required. Wi-Chase: A WiFi based Human Activity Recognition System for Sensorless Environments. A VAD classifies a piece of audio data as being voiced or unvoiced. For Python training, our top recommendation is DataCamp. Real time face recognition. He is always open to new technologies, able to learn quickly and apply the new knowledge in practice. View Alexei Kondratenko’s profile on LinkedIn, the world's largest professional community. Introduction. This list is the perfect guide for you to learn all the concepts required to clear a Python interview. TED began in 1984 as a conference where Technology, Entertainment and Design converged, and today covers almost all topics — from science to business to global issues — in more than 110 languages. Disclaimer nih. edu/job_detail/179251/assistant_to_the_dean The University of Michigan, School of Education seeks a high-level experienced individual to provide. Provided by Microsoft. Two new modalities are introduced for action recognition: warp flow and RGB diff. We aggregate information from all open source repositories. Training random forest classifier with scikit learn. But can computers converse too? Well, over the last few decades computers and humans have begun to interact with each other through speech…. L-System Compiler and Renderer in Python. suggest some good backlogs, combined with the given ones in the suggested section, and then sprints. Action recognition by dense trajectories by Wang et. com Abstract- Activity recognition is one of the leading application of machine learning algorithm nowadays. Which ones are they? They are the ones for which the OpenCV and SimpleCv developers have provided the execution of the training process and made both libraries available. We’re basically building artificial brains to analyze the data in order to figure out how the human brain works,” he says. Human activities are inherently translation invariant and hierarchical. It's 4433 Megabytes. This data set is collected from recordings of 30 human subjects captured via smartphones enabled with embedded inertial sensors. Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python [Denis Rothman, Matthew Lamons, Rahul Kumar, Abhishek Nagaraja, Amir Ziai, Ankit Dixit] on Amazon. of the 11th Mediterranean Conf. This is a final project demo of course EECS6895: Advanced big data analytics at Columbia University. As you can see, it is a rather complicated process. Any simple activity like brushing teeth, making breakfast, or reading a book will work. The critical acidic residues are conserved in plants and animals with the corresponding mutations impairing the enzyme activity of both JMJ14 and human KDM5B, indicating a common substrate recognition mechanism for KDM5 subfamily demethylases shared by plants and animals and further informing efforts to design targeted inhibitors of human KDM5. What username/password combinatios are allowed to connect to the honeypot? Searching for specific Data. Bao & Intille  developed an activity recognition system to identify twenty activities using bi-axial accelerometers placed in five locations on the user’s body. edu, [email protected]
Here's an introduction to the different techniques used in Human Pose Estimation based on Deep Learning. If it is present, mark it as a region of interest (ROI), extract the ROI and process it for facial recognition. Data includes RGB images of detections, estimated skeleton pose from depth sensor, robot odometry and ground truth segmentation and labelling of activities. • Working in PYTHON and Big Data Analytics • Worked in Image Processing project to improve image quality by applying mathematical operations. The HCML is an interdisciplinary resort that integrates engineering innovation with human health and human behaviors. In this paper, we introduce a hand gesture. Predicting Human Activity from Smartphone Accelerometer and Gyroscope Data. This monograph describes a biometric system that uses individual characteristics of human gait for authentication. wrnchAI is a real-time AI software platform that captures and digitizes human motion and behaviour from standard video. It’s an engine of human achievement. for video-based human activity recognition. This tutorial will give you a brief introduction of the Android Speech API used for voice recognition, which is an area of computational linguistics that develops methodologies and technologies automating recognition and translation of spoken language into text—Speech-to-Text (STT). Spatio-Temporal Phrases for Activity Recognition 3 between the words, while discarding the temporal ordering and spatial layout among them [6,13], and thus is incapable of modeling the casuality relationships. patterns of fMRI activity in human visual cortex Vision and Pattern Recognition. In addition to being one of the awardees of the last competition I organized, he won the Pascal 2 Challenge in Human Layout Recognition (2010). Welcome to My Activity. The majority of the code in this post is largely taken from Omid Alemi's simply elegant tutorial named "Build Your First Tensorflow Android App". activity detection. Its applications range from. Human activity understanding encompasses activity recognition and activity pattern discovery. Presented here is a project for a simple transistor’s output characteristic curve-tracer program through the serial interface and PIC microcontroller using Python programming language. Many videos depict people, and it is their interactions that inform us of their activities, relation to one another and the cultural and social setting. However, I was responding to the point about 1k doc's and 100k schemas and saying this was unnecessary, so don't shift the goal-posts. With this plugin you can easily install and use Ironclad CAPTCHA in your WordPress blog. Today we explore over 20 emotion recognition APIs and SDKs that can be used in projects to interpret a user’s mood. Implementing a CNN for Human Activity Recognition in Tensorflow In the recent years, we have seen a rapid increase in smartphones usage which are equipped with sophisticated sensors such as accelerometer and gyroscope etc. 5 Free Programming and Machine Learning Books for Data Scientists Growing as a data scientist is a massive investment of time and energy. How to use the speech module to use speech recognition and text-to-speech in Windows XP or Vista. It would be great if the library was in C, C++ or even Objective-C as I'm writing an app for the iPhone. Train the deep neural network for human activity recognition data; Validate the performance of the trained DNN against the test data using learning curve and confusion matrix; Export the trained Keras DNN model for Core ML; Ensure that the Core ML model was exported correctly by conducting a sample prediction in Python. Simple human activities have been elderly successfully recognized and researched so far. In this paper, we study the problem of activity recognition and abnormal behaviour detection for elderly people with dementia. Human Activity Recognition Codes and Scripts Downloads Free. applications if we can understand the human activity, for example, human activity understanding in daily scenes and activity based video indexing. Pattern recognition is one of the fundamental core problems in the field of cognitive psychology. The training and test datasets are provided. 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. Raspbian as OS) and Python, but. The project tasks shall be carried out individually. I would recommend Rasim as skilled research engineer with hand-on experience at algorithm and application development in Object/Gesture Recognition area. After registration user can login using face recognition. We include an intro to Python if you're new to it, but you'll need some prior programming experience in order to use this course successfully. Activity sensing and recognition have been demonstrated to be critical in health care and smart home applications. By now, you would have noticed several features of Facebook- ‘People You May Know’ and ‘Face Recognition’. Many videos depict people, and it is their interactions that inform us of their activities, relation to one another and the cultural and social setting. This capability implies that mechanisms to extract numerosity indwell the brain’s visual system, which is primarily concerned with visual object recognition. Video Analysis to Detect Suspicious Activity Based on Deep Learning Learn how to build on AI system that can classify a video into three classes: criminal or violent activity, potentially. VP8*-specific neutralizing activity can be detected in normal human adult sera using HT-29 but not MA104 cells. Tunçel, Comparative study on classifying human activities with miniature inertial and magnetic sensors, Pattern Recognition, 43(10):3605-3620, October 2010. We will explain in detail how to use a pre-trained Caffe model that won the COCO keypoints challenge in 2016 in your own application. Various algorithms that have been developed For pattern matching. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. However, they seem a little too complicated, out-dated and also require GStreamer dependency. View Canh Nguyen Xuan’s profile on LinkedIn, the world's largest professional community. Introduction to Machine Learning With Python. 3D Convolutional Neural Networks for Human Action Recognition by Ji et al. LRCN was accepted as an oral presentation at CVPR 2015. As a young Pythonista in the present year I find this a thoroughly unacceptable state of affairs, so I decided to write a crash course in how to build random forest models in Python using the machine learning library scikit-learn (or sklearn to friends). Project Organization Charts. Can we recognize Human Activity Using Single Chest-Mounted Accelerometer (Sensor)? Activity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. This time, we see much more better algorithms like “Meanshift”, and its upgraded version, “Camshift” to find and track them. The blockchain acts as a single source of truth, and members in a blockchain network can view only those transactions that are relevant to them. The complete data & related papers can be accessed at: UCI ML repository page. Raspbian as OS) and Python, but. Speech Recognition Systems. Human Activity Recognition. A VAD classifies a piece of audio data as being voiced or unvoiced. Kwapisz, Gary M. The reason for its importance is the abundance of applications that can benefit from such a technology. IEEE WoWMoM 2017. ü Your First Machine Learning Project in Python Step-By-Step. This data set is collected from recordings of 30 human subjects captured via smartphones enabled with embedded inertial sensors. Abstract: In this project, we calculate a model by which a smartphone can detect. DATABASES. ü How To Compare Machine Learning Algorithms in Python with scikit-learn. Moore (2010). CONVERSATIONAL INTERFACES – Speech Recognition Technology - Conversations are a part of our lives. - Setting up automated monitoring checks with sensu, grafana, elasticsearch, python, bash, etc - Maintaining Grafana / Graphite stack to provide real time access to metrics for large scale infrastructure. Skills: Engineering, Python. sg Abstract. Sign in to review and manage your activity, including things you’ve searched for, websites you’ve visited, and videos you’ve watched. Artificial intelligence is the ability of a machine to think, learn and perform tasks normally requiring human intelligence, such as visual perception, speech recognition and decision-making skills. One example: It’s now possible to record the activity of hundreds of thousands of neurons. This is the above mentioned paper. We will learn step by step, how to use a PiCam to recognize faces in real-time. LRCN was accepted as an oral presentation at CVPR 2015. Be Part of Ask A Biologist. "Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks. View Adeyinka Peace Adedigba’s profile on LinkedIn, the world's largest professional community. The trained model will be exported/saved and added to an Android app. The goal of the activity recognition is an automated analysis or interpretation of ongoing events and their context from video data. Moore (2010). Keywords: Machine-Learning, Time-Series, Sequences, Python 1. We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. Or copy & paste this link into an email or IM:. This unfortunately is what I see a lot of when I google 'speech detection'. Therefore, there's a need for a system which can recognize human activity effectively in real-time. Note: If u cant help with Python, please help with part 1, i. Human activity recognition (HAR), a field that has garnered a lot of attention in recent years due to its high demand in various application domains, makes use of time-series sensor data to infer activities. Artificial intelligence is the ability of a machine to think, learn and perform tasks normally requiring human intelligence, such as visual perception, speech recognition and decision-making skills. Provided by Microsoft. Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question. Moore (2010). Activity sensing and recognition have been demonstrated to be critical in health care and smart home applications. We will train an LSTM Neural Network (implemented in TensorFlow) for Human Activity Recognition (HAR) from accelerometer data. My argument is based on a recognition that what elements of a schema I need depends on what is the purpose of the XML document to which the schema refers. In the former project team Orion, we have developed two platforms, one (VSIP), a library of real-time video understanding modules and another one, Lama, a software platform enabling to design not only knowledge bases, but also inference engines, and additional tools. Python code. See our arXiv report for details on our approach. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. It had many recent successes in computer vision, automatic speech recognition and natural language processing. Human Activity Recognition Using Smartphones Data Set Download: Data Folder, Data Set Description. Each gesture is assigned to a specific action. Implementing the Handwritten digits recognition model Implementing the handwritten digits model using Tensorflow with Python. With an increase in investments in smart cities, smart healthcare, and industrial Internet of. See the complete profile on LinkedIn and discover Erinç’s connections and jobs at similar companies. Activity monitoring is one of the predominant concerns of the elderly living at home. In this paper, a total of thirty-two recent research papers on sensing technologies used in HAR are reviewed. The Python affine6p lib to estimate affine transformation parameters between two sets of 2D points. H SBC will become the first bank in the UK to roll out voice recognition technology for its telephone banking system to every customer, and it has also embraced fingerprint scanners for its. Face recognition application based on Python and OpenCV library which was able to recognize human faces. Activity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. The World Wide Web (abbreviated as WWW or W3,  commonly known as the Web) is a system of interlinked hypertext documents that are accessed via the Internet. When we're talking about displaying information to a human, XHTML is the *destination*. Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.