PyData LA 2018 I will present some way in which tensor methods can be combined with deep learning, and demonstrate through Jupyter notebooks on how easy it is specify tensorized neural networks. — PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Why do people collaborate? Because we achieve more together than we can alone. The same is true of man and machine. Leaders need to add machine learning to their data and analytics strategies to unlock actionable insights that help employees make better business decisions. This is augmented intelligence. In the sixth installment of his “Journeys in Transformation” webchat series, Genpact’s Chief Digital Officer, Sanjay Srivastava, shares a framework for augmented intelligence. Joining him are: • JoAnn Stonier, Chief Data Officer at MasterCard • Henna Karna, Chief Data Officer at AXA XL • Vikram Mahidhar, Leader, AI Growth Strategy at Genpact
** Edureka Python Certification Training: ** This Edureka video on ‘Robot Framework With Python’ explains the various aspects of robot framework in python with a use case showing web testing using selenium library. Following are the topics discussed in this Robot Framework Tutorial: What is Robot Framework In Python? Standard Libraries Built-in Tools Test Cases Keywords Variables Organizing Test Cases Use Case – RobotFramework-SeleniumLibrary Python Tutorial Playlist: Blog Series: #PythonEdureka #Edureka #robotframeworkinpython #pythonprojects #pythonprogramming #pythontutorial #PythonTraining Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: Instagram: Facebook: Twitter: LinkedIn: ———————————————————————————————————————————– How it Works? 1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! – – – – – – – – – – – – – – – – – About the Course Edureka’s Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help [More]
This Deep Learning tutorial covers all the essential Deep Learning frameworks that are necessary to build AI models. In this video, you will learn about the development of essential frameworks such as TensorFlow, Keras, PyTorch, Theano, etc. You will also understand the programming languages used to build the frameworks, the different companies that use these frameworks, the characteristics of these Deep Learning frameworks, and type of models that were built using these frameworks. Now, let us get started with understanding the different popular Deep Learning frameworks being used in industries. Below are the different Deep Learning frameworks we’ll be discussing in this video: 1. TensorFlow (01:28) 2. Keras (02:54) 3. PyTorch (05:02) 4. Theano (06:30) 5. Deep Learning 4 Java (07:55) 6. Caffe (09:51) 7. Chainer (11:29) 8. Microsoft CNTK (13:48) To learn more about Deep Learning, subscribe to our YouTube channel: To access the slides, click here: Watch more videos on Deep Learning: #DeepLearningFrameworks #DeepLearningTutorial #DeepLearning #Datasciencecourse #DataScience #SimplilearnMachineLearning #DeepLearningCourse Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you’ll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as deep learning scientist. Why Deep Learning? It is one of the most popular software platforms used [More]
Winter Intelligence Oxford – Organized by the Future of Humanity Institute – AGI12 – ==The Next Generation of the MicroPsi Framework== Joscha Bach, Humboldt University of Berlin, Germany
( ** AI & Deep Learning with Tensorflow Training: ** ) This Edureka video on “Deep Learning Frameworks” ( provides you an insight into the top 8 Deep Learning frameworks you should consider learning 00:38 Chainer 01:40 CNTK 03:12 Caffe 04:46 MXNet 05:55 Deeplearning4j 07:42 Keras 09:21 PyTorch 10:45 TensorFlow 12:10 Conclusion Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: Check out our Deep Learning blog series: Check out our complete Youtube playlist here: ————————————- Instagram: Facebook: Twitter: LinkedIn: #PyTorch #TensorFlow #DeepLearning #Python ————————————- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. About the Course Edureka’s Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course [More]