Search results for "deeplearning4j"

26 documents found out of 7074 total.

• 10 GitHub Repositories to Master Machine Learning Deployment

  Master the essential skill of deploying machine learning models with courses, projects, examples, resources, and interview questions.

  https://www.kdnuggets.com/10-github-repositories-to-master-machine-learning-deployment

• Top 6 Reasons Data Scientists Should Know Java

  There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.

  https://www.kdnuggets.com/2020/06/top-6-reasons-data-scientists-know-java.html

• Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis">Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis

  Python continues to lead the top Data Science platforms, but R and RapidMiner hold their share; Almost 50% have used Deep Learning tools; SQL is steady; Consolidation continues.

  https://www.kdnuggets.com/2019/05/poll-top-data-science-machine-learning-platforms.html

• Which Deep Learning Framework is Growing Fastest?

  In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed?

  https://www.kdnuggets.com/2019/05/which-deep-learning-framework-growing-fastest.html

• Building a Question-Answering System from Scratch

  This part will focus on introducing Facebook sentence embeddings and how it can be used in building QA systems. In the future parts, we will try to implement deep learning techniques, specifically sequence modeling for this problem.

  https://www.kdnuggets.com/2018/10/building-question-answering-system-from-scratch.html

• Deep Learning Framework Power Scores 2018

  Who’s on top in usage, interest, and popularity?

  https://www.kdnuggets.com/2018/09/deep-learning-framework-power-scores-2018.html

• Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis">Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis

  Python continues to eat away at R, RapidMiner gains, SQL is steady, Tensorflow advances pulling along Keras, Hadoop drops, Data Science platforms consolidate, and more.

  https://www.kdnuggets.com/2018/05/poll-tools-analytics-data-science-machine-learning-results.html

• Top 16 Open Source Deep Learning Libraries and Platforms

  We bring to you the top 16 open source deep learning libraries and platforms. TensorFlow is out in front as the undisputed number one, with Keras and Caffe completing the top three.

  https://www.kdnuggets.com/2018/04/top-16-open-source-deep-learning-libraries.html

• A “Weird” Introduction to Deep Learning">A “Weird” Introduction to Deep Learning

  There are amazing introductions, courses and blog posts on Deep Learning. But this is a different kind of introduction.

  https://www.kdnuggets.com/2018/03/weird-introduction-deep-learning.html

• Where AI is already rivaling humans

  Since 2011, AI hit hypergrowth, and researchers have created several AI solutions that are almost as good as – or better than – humans in several domains, including games, healthcare, computer vision and object recognition, speech to text conversion, speaker recognition, and improved robots and chat-bots for solving specific problems.

  https://www.kdnuggets.com/2018/02/domains-ai-rivaling-humans.html

• Ranking Popular Deep Learning Libraries for Data Science">Ranking Popular Deep Learning Libraries for Data Science

  We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.

  https://www.kdnuggets.com/2017/10/ranking-popular-deep-learning-libraries-data-science.html

• 37 Reasons why your Neural Network is not working">37 Reasons why your Neural Network is not working

  Over the course of many debugging sessions, I’ve compiled my experience along with the best ideas around in this handy list. I hope they would be useful to you.

  https://www.kdnuggets.com/2017/08/37-reasons-neural-network-not-working.html

• How Convolutional Neural Networks Accomplish Image Recognition?

  Image recognition is very interesting and challenging field of study. Here we explain concepts, applications and techniques of image recognition using Convolutional Neural Networks.

  https://www.kdnuggets.com/2017/08/convolutional-neural-networks-image-recognition.html

• Data Science & Machine Learning Platforms for the Enterprise

  A resilient Data Science Platform is a necessity to every centralized data science team within a large corporation. It helps them centralize, reuse, and productionize their models at peta scale.

  https://www.kdnuggets.com/2017/05/data-science-machine-learning-platforms-enterprise.html

• Getting Started with Deep Learning

  This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.

  https://www.kdnuggets.com/2017/03/getting-started-deep-learning.html

• Questions To Ask When Moving Machine Learning From Practice to Production

  An overview of applying machine learning techniques to solve problems in production. This articles covers some of the varied questions to ponder when incorporating machine learning into teams and processes.

  https://www.kdnuggets.com/2016/11/moving-machine-learning-practice-production.html

• How Convolutional Neural Networks Work

  Get an overview of what is going on inside convolutional neural networks, and what it is that makes them so effective.

  https://www.kdnuggets.com/2016/08/brohrer-convolutional-neural-networks-explanation.html

• Top Machine Learning Libraries for Javascript

  Javascript may not be the conventional choice for machine learning, but there is no reason it cannot be used for such tasks. Here are the top libraries to facilitate machine learning in Javascript.

  https://www.kdnuggets.com/2016/06/top-machine-learning-libraries-javascript.html

• R, Python Duel As Top Analytics, Data Science software – KDnuggets 2016 Software Poll Results

  R remains the leading tool, with 49% share, but Python grows faster and almost catches up to R. RapidMiner remains the most popular general Data Science platform. Big Data tools used by almost 40%, and Deep Learning usage doubles.

  https://www.kdnuggets.com/2016/06/r-python-top-analytics-data-mining-data-science-software.html

• Top 10 Deep Learning Projects on Github

  The top 10 deep learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.

  https://www.kdnuggets.com/2016/01/top-10-deep-learning-github.html

• 7 Steps to Understanding Deep Learning

  There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!

  https://www.kdnuggets.com/2016/01/seven-steps-deep-learning.html

• DeepLearningKit – Open Source Deep Learning Framework for Apple iOS, OS X

  We are introducing you to the new deep learning framework “DeepLearningKit”, for the Apple based OS which is developed in Metal and Swift.

  https://www.kdnuggets.com/2015/12/deeplearningkit-open-source-framework-apple-ios-osx.html

• 50 Deep Learning Software Tools and Platforms, Updated

  We present the popular software & toolkit resources for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch. Explore the new list!

  https://www.kdnuggets.com/2015/12/deep-learning-tools.html

• Popular Deep Learning Tools – a review

  Deep Learning is the hottest trend now in AI and Machine Learning. We review the popular software for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch.

  https://www.kdnuggets.com/2015/06/popular-deep-learning-tools.html

• R leads RapidMiner, Python catches up, Big Data tools grow, Spark ignites

  R is the most popular overall tool among data miners, although Python usage is growing faster. RapidMiner continues to be most popular suite for data mining/data science. Hadoop/Big Data tools usage grew to 29%, propelled by 3x growth in Spark. Other tools with strong growth include H2O (0xdata), Actian, MLlib, and Alteryx.

  https://www.kdnuggets.com/2015/05/poll-r-rapidminer-python-big-data-spark.html

• Machine Learning Table of Elements Decoded

  Machine learning packages for Python, Java, Big Data, Lua/JS/Clojure, Scala, C/C++, CV/NLP, and R/Julia are represented using a cute but ill-fitting metaphor of a periodic table. We extract the useful links.

  https://www.kdnuggets.com/2015/03/machine-learning-table-elements.html