1D Convolutional Neural Networks for Time Series Modeling - Nathan Janos, Jef...PyData
This talk describes an experimental approach to time series modeling using 1D convolution filter layers in a neural network architecture. This approach was developed at System1 for forecasting marketplace value of online advertising categories.
Java Programming | Java Tutorial For Beginners | Java Training | EdurekaEdureka!
This Edureka Java Programming tutorial will help you in understanding the various programming fundamentals of Java in detail with examples. Below are the topics covered in this tutorial:
1) Variables
2) Data Types in Java
3) Operators in Java
4) Conditional Statements in Java
5) Loops
6) Arrays and Strings
7) Functions in Java
8) Classes and Objects in Java
https://telecombcn-dl.github.io/2017-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...Taegyun Jeon
PR-050: Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Original Slide from http://home.cse.ust.hk/~xshiab/data/valse-20160323.pptx
Youtube: https://youtu.be/3cFfCM4CXws
My presentation in SDCC 2012 (http://sdcc.csdn.net/index_en.html). The video recording of this session is available at http://v.csdn.hudong.com/s/article.html?arcid=2810640
In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. The basic SVM takes a set of input data and predicts, for each given input, which of two possible classes forms the output, making it a non-probabilistic binary linear classifier.
In this core java training session, you will learn Handling Strings in Java. Topics covered in this session are:
• Memory Allocation & Garbage Collection
• Strings in Java
For more information about this course visit on this link: https://www.mindsmapped.com/courses/software-development/learn-java-fundamentals-hands-on-training-on-core-java-concepts/
This slide introduces transformer-xl which is the base paper for xl-net. You can understand what is the major contribution of this paper using this slide. This slide also explains the transformer for comparing differences between transformer and transformer-xl. Happy NLP!
Basics covered regarding Natural Language Processing, How ANN transformed to RNN, Architectures of vanila RNN, LSTM and GRU and few preprocessing techniques
Super keyword is a reference variable that is used for refer parent class object. Super keyword is used in java at three level, at variable level, at method level and at constructor level.
In this tutorial, we will learn the the following topics -
+ Linear SVM Classification
+ Soft Margin Classification
+ Nonlinear SVM Classification
+ Polynomial Kernel
+ Adding Similarity Features
+ Gaussian RBF Kernel
+ Computational Complexity
+ SVM Regression
Data abstraction is the process of hiding certain details and showing only essential information to the user.
Interfaces and Abstract classes.
Contains abstract keyword also.
1D Convolutional Neural Networks for Time Series Modeling - Nathan Janos, Jef...PyData
This talk describes an experimental approach to time series modeling using 1D convolution filter layers in a neural network architecture. This approach was developed at System1 for forecasting marketplace value of online advertising categories.
Java Programming | Java Tutorial For Beginners | Java Training | EdurekaEdureka!
This Edureka Java Programming tutorial will help you in understanding the various programming fundamentals of Java in detail with examples. Below are the topics covered in this tutorial:
1) Variables
2) Data Types in Java
3) Operators in Java
4) Conditional Statements in Java
5) Loops
6) Arrays and Strings
7) Functions in Java
8) Classes and Objects in Java
https://telecombcn-dl.github.io/2017-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...Taegyun Jeon
PR-050: Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Original Slide from http://home.cse.ust.hk/~xshiab/data/valse-20160323.pptx
Youtube: https://youtu.be/3cFfCM4CXws
My presentation in SDCC 2012 (http://sdcc.csdn.net/index_en.html). The video recording of this session is available at http://v.csdn.hudong.com/s/article.html?arcid=2810640
In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. The basic SVM takes a set of input data and predicts, for each given input, which of two possible classes forms the output, making it a non-probabilistic binary linear classifier.
In this core java training session, you will learn Handling Strings in Java. Topics covered in this session are:
• Memory Allocation & Garbage Collection
• Strings in Java
For more information about this course visit on this link: https://www.mindsmapped.com/courses/software-development/learn-java-fundamentals-hands-on-training-on-core-java-concepts/
This slide introduces transformer-xl which is the base paper for xl-net. You can understand what is the major contribution of this paper using this slide. This slide also explains the transformer for comparing differences between transformer and transformer-xl. Happy NLP!
Basics covered regarding Natural Language Processing, How ANN transformed to RNN, Architectures of vanila RNN, LSTM and GRU and few preprocessing techniques
Super keyword is a reference variable that is used for refer parent class object. Super keyword is used in java at three level, at variable level, at method level and at constructor level.
In this tutorial, we will learn the the following topics -
+ Linear SVM Classification
+ Soft Margin Classification
+ Nonlinear SVM Classification
+ Polynomial Kernel
+ Adding Similarity Features
+ Gaussian RBF Kernel
+ Computational Complexity
+ SVM Regression
Data abstraction is the process of hiding certain details and showing only essential information to the user.
Interfaces and Abstract classes.
Contains abstract keyword also.
One Size Doesn't Fit All: The New Database Revolutionmark madsen
Slides from a webcast for the database revolution research report (report will be available at http://www.databaserevolution.com)
Choosing the right database has never been more challenging, or potentially rewarding. The options available now span a wide spectrum of architectures, each of which caters to a particular workload. The range of pricing is also vast, with a variety of free and low-cost solutions now challenging the long-standing titans of the industry. How can you determine the optimal solution for your particular workload and budget? Register for this Webcast to find out!
Robin Bloor, Ph.D. Chief Analyst of the Bloor Group, and Mark Madsen of Third Nature, Inc. will present the findings of their three-month research project focused on the evolution of database technology. They will offer practical advice for the best way to approach the evaluation, procurement and use of today’s database management systems. Bloor and Madsen will clarify market terminology and provide a buyer-focused, usage-oriented model of available technologies.
Webcast video and audio will be available on the report download site as well.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
Streamlining Technology to Reduce Complexity and Improve ProductivityKevin Fream
The 3 biggest challenges for mid-sized companies are: clutter, discovery, and curiosity. Those that thrive will become experts in streamlining technology while remaining vigilant in following new trends.
Power of Code: What you don’t know about what you knowcdathuraliya
Introductory and inspiring session for students on computer science
Date: 19th March 2013
Event: IT workshop for high school students
Venue: President's College, Maharagama
Organized by: Society of Computer Science, University of Sri Jayewardenepura