Tag: Deep Learning (856)

• Which Data Science Skills are core and which are hot/emerging ones? - Sep 17, 2019.
  
  We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

  Tags: Career, Data Science Skills, Data Visualization, Deep Learning, Excel, Machine Learning, Python, PyTorch, Scala, Skills, Statistics, TensorFlow

• 5 Step Guide to Scalable Deep Learning Pipelines with d6tflow - Sep 16, 2019.
  
  How to turn a typical pytorch script into a scalable d6tflow DAG for faster research & development.

  Tags: Deep Learning, Pipeline, Python, PyTorch, Workflow

• A 2019 Guide to Speech Synthesis with Deep Learning - Sep 9, 2019.
  
  In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.

  Tags: Deep Learning, NLP, Speech

• KDnuggets™ News 19:n33, Sep 4: Data Science Skills Poll; Object-oriented Programming for Data Scientists - Sep 4, 2019.
  
  This week: Object-oriented programming for data scientists; Deep Learning Next Step: Transformers and Attention Mechanism; R Users' Salaries from the 2019 Stackoverflow Survey; Types of Bias in Machine Learning; 4 Tips for Advanced Feature Engineering and Preprocessing; and much more!

  Tags: Data Science, Data Science Skills, Deep Learning, NLP, Poll, Programming, R, Salary

• TensorFlow vs PyTorch vs Keras for NLP - Sep 3, 2019.
  
  These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.

  Tags: Deep Learning, Exxact, Keras, NLP, PyTorch, TensorFlow

• Deep Learning Next Step: Transformers and Attention Mechanism - Aug 29, 2019.
  
  With the pervasive importance of NLP in so many of today's applications of deep learning, find out how advanced translation techniques can be further enhanced by transformers and attention mechanisms.

  Tags: Attention, Deep Learning, NLP, Transformer

• TensorFlow 2.0: Dynamic, Readable, and Highly Extended - Aug 27, 2019.
  
  With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.

  Tags: Deep Learning, Deployment, Exxact, TensorFlow

• Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference? - Aug 26, 2019.
  
  Over the past few years, artificial intelligence continues to be one of the hottest topics. And in order to work effectively with it, you need to understand its constituent parts.

  Tags: AI, Deep Learning, Machine Learning

• Deep Learning for NLP: Creating a Chatbot with Keras! - Aug 19, 2019.
  
  Learn how to use Keras to build a Recurrent Neural Network and create a Chatbot! Who doesn’t like a friendly-robotic personal assistant?

  Tags: Chatbot, Deep Learning, Keras, NLP, Python

• Top KDnuggets tweets, Aug 07-13: Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners To Follow - Aug 14, 2019.
  
  Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs.

  Tags: Deep Learning, Graph Mining, NLP, Top tweets

• KDnuggets™ News 19:n30, Aug 14: Know Your Neighbor: Machine Learning on Graphs; 12 NLP Researchers, Practitioners You Should Follow - Aug 14, 2019.
  
  Machine Learning on Graphs; 12 amazing leaders in NLP; Deep Learning for NLP explained, including ANNs, RNNs and LSTMs; Benford's Law and why is it important for data science; Key concepts in Andrew Ng "Machine Learning Yearning".

  Tags: Andrew Ng, Benford's Law, Deep Learning, Graph Mining, NLP

• Postdoctoral position (2 years) in multivariate analysis and deep learning [Umeå, Sweden] - Aug 13, 2019.
  
  Help develop new e-science methods that fundamentally integrates Deep Learning and Multivariate analysis. The postdoc position is full-time for a period of two years

  Tags: Deep Learning, Multivariate Testing, Postdoc, Sweden, Umea University

• Deep Learning for NLP: ANNs, RNNs and LSTMs explained! - Aug 7, 2019.
  
  Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!

  Tags: Deep Learning, Explained, LSTM, Neural Networks, NLP, Recurrent Neural Networks

• Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree - Aug 2, 2019.
  
  This cheatsheet should be easier to digest than the official documentation and should be a transitional tool to get students and beginners to get started reading documentations soon.

  Tags: Beginners, Cheat Sheet, CoLaboratory, Deep Learning, Python, PyTorch, Udacity

• Easily Deploy Deep Learning Models in Production - Aug 1, 2019.
  
  Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. This blog explores how to navigate these challenges.

  Tags: Deep Learning, Deployment, GPU, Inference, NVIDIA

• How a simple mix of object-oriented programming can sharpen your deep learning prototype - Aug 1, 2019.
  
  By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.

  Tags: Deep Learning, Keras, Programming, Python

• Here’s how you can accelerate your Data Science on GPU - Jul 30, 2019.
  
  Data Scientists need computing power. Whether you’re processing a big dataset with Pandas or running some computation on a massive matrix with Numpy, you’ll need a powerful machine to get the job done in a reasonable amount of time.

  Tags: Big Data, Data Science, Deep Learning, GPU, NVIDIA, Python

• A Gentle Introduction to Noise Contrastive Estimation - Jul 25, 2019.
  
  Find out how to use randomness to learn your data by using Noise Contrastive Estimation with this guide that works through the particulars of its implementation.

  Tags: Deep Learning, Logistic Regression, Neural Networks, Noise, Random, Sampling, word2vec

• This New Google Technique Help Us Understand How Neural Networks are Thinking - Jul 24, 2019.
  
  Recently, researchers from the Google Brain team published a paper proposing a new method called Concept Activation Vectors (CAVs) that takes a new angle to the interpretability of deep learning models.

  Tags: Accuracy, Deep Learning, Google, Interpretability, Neural Networks

• KDnuggets™ News 19:n27, Jul 24: Bayesian deep learning and near-term quantum computers; DeepMind’s CASP13 Protein Folding Upset Summary - Jul 24, 2019.
  
  This week on KDnuggets: Learn how DeepMind dominated the last CASP competition for advancing protein folding models; Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning; The Evolution of a ggplot; Adapters: A Compact and Extensible Transfer Learning Method for NLP; 12 Things I Learned During My First Year as a Machine Learning Engineer; Things I Learned From the SciPy 2019 Lightning Talks; and much more!

  Tags: Bayesian, Deep Learning, DeepMind, Kaggle, Machine Learning Engineer, NLP, Quantum Computing, SciPy, Transfer Learning

• A Summary of DeepMind’s Protein Folding Upset at CASP13 - Jul 17, 2019.
  
  Learn how DeepMind dominated the last CASP competition for advancing protein folding models. Their approach using gradient descent is today's state of the art for predicting the 3D structure of a protein knowing only its comprising amino acid compounds.

  Tags: Bioinformatics, Deep Learning, DeepMind, Exxact, Generative Adversarial Network, Gradient Descent, Protein

• Computer Vision for Beginners: Part 1 - Jul 17, 2019.
  
  Image processing is performing some operations on images to get an intended manipulation. Think about what we do when we start a new data analysis. We do some data preprocessing and feature engineering. It’s the same with image processing.

  Tags: Computer Vision, Deep Learning, Image Processing, Python

• Scaling a Massive State-of-the-art Deep Learning Model in Production - Jul 15, 2019.
  
  A new NLP text writing app based on OpenAI's GPT-2 aims to write with you -- whenever you ask. Find out how the developers setup and deployed their model into production from an engineer working on the team.

  Tags: Deep Learning, Deployment, NLP, OpenAI, Scalability, Transformer

• Cartoon: AI + Self-Driving + BBQ = ? - Jul 4, 2019.
  
  KDnuggets Cartoon looks at what happens when AI and self-driving technology collide with the traditional summer pastime of grilling.

  Tags: Adversarial, Cartoon, Deep Learning, Self-Driving Car

• Nvidia’s New Data Science Workstation — a Review and Benchmark - Jul 3, 2019.
  
  Nvidia has recently released their Data Science Workstation, a PC that puts together all the Data Science hardware and software into one nice package. The workstation is a total powerhouse machine, packed with all the computing power — and software — that’s great for plowing through data.

  Tags: Advice, Big Data, Deep Learning, GPU, NVIDIA

• Examining the Transformer Architecture – Part 2: A Brief Description of How Transformers Work - Jul 2, 2019.
  
  As The Transformer may become the new NLP standard, this review explores its architecture along with a comparison to existing approaches by RNN.

  Tags: BERT, Deep Learning, Exxact, GPU, NLP, Recurrent Neural Networks, Transfer Learning, Transformer

• An Overview of Human Pose Estimation with Deep Learning - Jun 28, 2019.
  
  Human Pose Estimation is one of the main research areas in computer vision. The reason for its importance is the abundance of applications that can benefit from such a technology. Here's an introduction to the different techniques used in Human Pose Estimation based on Deep Learning.

  Tags: Computer Vision, Convolutional Neural Networks, Deep Learning, Image Recognition, Object Detection

• PySyft and the Emergence of Private Deep Learning - Jun 27, 2019.
  
  PySyft is an open-source framework that enables secured, private computations in deep learning, by combining federated learning and differential privacy in a single programming model integrated into different deep learning frameworks such as PyTorch, Keras or TensorFlow.

  Tags: Deep Learning, Differential Privacy, Privacy, Python, Security

• 10 Gradient Descent Optimisation Algorithms + Cheat Sheet - Jun 26, 2019.
  
  Gradient descent is an optimization algorithm used for minimizing the cost function in various ML algorithms. Here are some common gradient descent optimisation algorithms used in the popular deep learning frameworks such as TensorFlow and Keras.

  Tags: Algorithms, Deep Learning, Gradient Descent, Optimization

• Why do we need AWS SageMaker? - Jun 26, 2019.
  
  Today, there are several platforms available in the industry that aid software developers, data scientists as well as a layman in developing and deploying machine learning models within no time.

  Tags: AWS, Cloud Computing, Data Science, Deep Learning, Jupyter, Machine Learning, Sagemaker

• Do Conv-nets Dream of Psychedelic Sheep? - Jun 25, 2019.
  
  In deep learning, understanding your model well enough to interpret its behavior will help improve model performance and reduce the black-box mystique of neural networks.

  Tags: Convolutional Neural Networks, Data Visualization, Deep Learning, Exxact

• 10 New Things I Learnt from fast.ai Course V3 - Jun 24, 2019.
  
  Fastai offers some really good courses in machine learning and deep learning for programmers. I recently took their "Practical Deep Learning for Coders" course and found it really interesting. Here are my learnings from the course.

  Tags: Deep Learning, fast.ai, Jeremy Howard, Machine Learning, MOOC

• How to Automate Hyperparameter Optimization - Jun 12, 2019.
  
  A step-by-step guide into performing a hyperparameter optimization task on a deep learning model by employing Bayesian Optimization that uses the Gaussian Process. We used the gp_minimize package provided by the Scikit-Optimize (skopt) library to perform this task.

  Tags: Bayesian, Deep Learning, Hyperparameter, Machine Learning, Neural Networks, Optimization, Python, TensorFlow

• What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem - Jun 10, 2019.
  
  We identify the 6 tools in the modern open-source Data Science ecosystem, examine the Python vs R question, and determine which tools are used the most with Deep Learning and Big Data.

  Tags: Anaconda, Apache Spark, Big Data Software, Deep Learning, Excel, Keras, Poll, Python, R, RapidMiner, scikit-learn, Software, SQL, Tableau, TensorFlow

• Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis - May 30, 2019.
  
  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.

  Pages: 1 2

  Tags: Anaconda, Apache Spark, Deep Learning, Excel, Keras, Poll, Python, R, RapidMiner, scikit-learn, Software, SQL, TensorFlow

• How the Lottery Ticket Hypothesis is Challenging Everything we Knew About Training Neural Networks - May 30, 2019.
  
  The training of machine learning models is often compared to winning the lottery by buying every possible ticket. But if we know how winning the lottery looks like, couldn’t we be smarter about selecting the tickets?

  Tags: Deep Learning, Lottery, Machine Learning, Neural Networks, Training Data

• 3 Machine Learning Books that Helped me Level Up as a Data Scientist - May 28, 2019.
  
  Each of these books has helped me immensely in different stages of my career as a Data Scientist, particularly in my role as a Machine Learning Engineer.

  Tags: Books, Data Science, Deep Learning, Machine Learning

• Analyzing Tweets with NLP in Minutes with Spark, Optimus and Twint - May 24, 2019.
  
  Social media has been gold for studying the way people communicate and behave, in this article I’ll show you the easiest way of analyzing tweets without the Twitter API and scalable for Big Data.

  Pages: 1 2

  Tags: Apache Spark, Big Data, Deep Learning, Machine Learning, NLP, Optimus, Python, Twint

• Extracting Knowledge from Knowledge Graphs Using Facebook’s Pytorch-BigGraph - May 22, 2019.
  
  We are using the state-of-the-art Deep Learning tools to build a model for predict a word using the surrounding words as labels.

  Pages: 1 2

  Tags: Deep Learning, Facebook, Machine Learning, NLP, Python, PyTorch, word2vec

• Building a Computer Vision Model: Approaches and datasets - May 20, 2019.
  
  How can we build a computer vision model using CNNs? What are existing datasets? And what are approaches to train the model? This article provides an answer to these essential questions when trying to understand the most important concepts of computer vision.

  Tags: AI, Computer Vision, Deep Learning, ImageNet, Machine Learning, Neural Networks

• Autoencoders: Deep Learning with TensorFlow’s Eager Execution - May 20, 2019.
  
  Deep Learning has revolutionized the Machine Learning scene in the last years. Can we apply it to image compression? How well can a Deep Learning algorithm reconstruct pictures of kittens? What’s an autoencoder?

  Tags: Autoencoder, Deep Learning, Neural Networks, Python, TensorFlow

• Think Like an Amateur, Do As an Expert: Lessons from a Career in Computer Vision - May 17, 2019.
  
  Dr. Takeo Kanade shared his life lessons from an illustrious 50-year career in Computer Vision at last year's Embedded Vision Summit. You have a chance to attend the 2019 Embedded Vision Summit, from May 20-23, in the Santa Clara Convention Center, Santa Clara CA.

  Tags: AI, Algorithms, Computer Vision, Deep Learning, Machine Learning

• What’s Going to Happen this Year in the Data World - May 14, 2019.
  
  "If we wish to foresee the future of mathematics, our proper course is to study the history and present condition of the science." Henri Poncairé.

  Tags: Advice, AI, Big Data, Data Science, Deep Learning

• Books on Graph-Powered Machine Learning, Graph Databases, Deep Learning for Search – 50% off - May 9, 2019.
  
  These 3 books will help you make the most from graph-powered databases. For a limited time, get 50% off any of them with the code kdngraph.

  Tags: Book, Deep Learning, Graph Databases, Machine Learning, Manning, Search

• 2019 KDnuggets Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? - May 7, 2019.
  
  Vote in KDnuggets 20th Annual Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? We will publish the anon data, results, and trends here.

  Tags: Big Data, Data Mining Software, Data Science, Deep Learning, Machine Learning, Poll, Programming Languages

• Which Deep Learning Framework is Growing Fastest? - May 1, 2019.
  
  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?

  Tags: Data Science, Data Scientist, Deep Learning, fast.ai, Keras, Python, PyTorch, TensorFlow

• Top Data Science and Machine Learning Methods Used in 2018, 2019 - Apr 29, 2019.
  
  Once again, the most used methods are Regression, Clustering, Visualization, Decision Trees/Rules, and Random Forests. The greatest relative increases this year are overwhelmingly Deep Learning techniques, while SVD, SVMs and Association Rules show the greatest decline.

  Tags: Algorithms, Clustering, Data Science, Deep Learning, Machine Learning, Poll, Regression

• Meet the World’s Leading AI & Deep Learning Experts - Apr 25, 2019.
  
  RE-WORK returns to San Francisco Jun 20-21 with the Deep Reinforcement Learning Summit, the Applied AI Summit and the AI for Good Summit. KDnuggets subscribers get 20% off Early Bird discounted passes when you register before May 3 with code KDNUGGETS.

  Tags: AI, CA, Deep Learning, RE.WORK, San Francisco

• Graduating in GANs: Going From Understanding Generative Adversarial Networks to Running Your Own - Apr 25, 2019.
  
  Read how generative adversarial networks (GANs) research and evaluation has developed then implement your own GAN to generate handwritten digits.

  Pages: 1 2

  Tags: Deep Learning, GANs, Generative Adversarial Network, Generative Models, MNIST, Neural Networks, Python

• Attention Craving RNNS: Building Up To Transformer Networks - Apr 24, 2019.
  
  RNNs let us model sequences in neural networks. While there are other ways of modeling sequences, RNNs are particularly useful. RNNs come in two flavors, LSTMs (Hochreiter et al, 1997) and GRUs (Cho et al, 2014)

  Pages: 1 2

  Tags: AI, Data Science, Deep Learning, Neural Networks, Recurrent Neural Networks, Transformer

• Approach pre-trained deep learning models with caution - Apr 23, 2019.
  
  Pre-trained models are easy to use, but are you glossing over details that could impact your model performance?

  Tags: Best Practices, Deep Learning, Training

• Earn a Deep Learning Certificate - Apr 22, 2019.
  
  Now is your chance to break into AI, even if you don’t have a PhD. If you want a job in AI and Deep Learning, Andrew Ng’s Specialization will help you get there.

  Tags: Andrew Ng, Coursera, Deep Learning, MOOC

• Hot Deep Learning Applications at Deep Learning World – Las Vegas, June 16-20 - Apr 15, 2019.
  
  Deep Learning World 2019, Jun 16-20 in Las Vegas, will cover a good portion of the wide range of deep learning application areas. Regular prices available until Apr 26. Register now!

  Tags: Deep Learning, Las Vegas, NV, PAW, Predictive Analytics World

• Another 10 Free Must-See Courses for Machine Learning and Data Science - Apr 5, 2019.
  
  Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.

  Tags: AI, Data Science, Deep Learning, Keras, Machine Learning, NLP, Reinforcement Learning, TensorFlow, U. of Washington, UC Berkeley, Unsupervised Learning

• Training a Champion: Building Deep Neural Nets for Big Data Analytics - Apr 4, 2019.
  
  Introducing Sisense Hunch, the new way of handling Big Data sets that uses AQP technology to construct Deep Neural Networks (DNNs) which are trained to learn the relationships between queries and their results in these huge datasets.

  Tags: Big Data Analytics, Deep Learning, Neural Networks, Sisense, SQL

• Which Face is Real? - Apr 2, 2019.
  
  Which Face Is Real? was developed based on Generative Adversarial Networks as a web application in which users can select which image they believe is a true person and which was synthetically generated. The person in the synthetically generated photo does not exist.

  Tags: Deep Learning, GANs, Generative Adversarial Network, Neural Networks, NVIDIA, Python

• The Deep Learning Toolset — An Overview - Mar 28, 2019.
  
  We are observing an increasing number of great tools that help facilitate the intricate process that is deep learning, making it both more accessible and more efficient.

  Tags: Advice, AI, Data Science, Data Scientist, Deep Learning

• Pedestrian Detection in Aerial Images Using RetinaNet - Mar 26, 2019.
  
  Object Detection in Aerial Images is a challenging and interesting problem. By using Keras to train a RetinaNet model for object detection in aerial images, we can use it to extract valuable information.

  Tags: AI, Computer Vision, Deep Learning, Keras, Object Detection, Retina Net

• Feature Reduction using Genetic Algorithm with Python - Mar 25, 2019.
  
  This tutorial discusses how to use the genetic algorithm (GA) for reducing the feature vector extracted from the Fruits360 dataset in Python mainly using NumPy and Sklearn.

  Pages: 1 2

  Tags: Deep Learning, Feature Engineering, Genetic Algorithm, Neural Networks, numpy, Python, scikit-learn

• Deep Compression: Optimization Techniques for Inference & Efficiency - Mar 20, 2019.
  
  We explain deep compression for improved inference efficiency, mobile applications, and regularization as technology cozies up to the physical limits of Moore's law.

  Tags: Compression, Convolutional Neural Networks, Deep Learning, ICLR, Inference, Optimization, Regularization

• Deploy your PyTorch model to Production - Mar 20, 2019.
  
  This tutorial aims to teach you how to deploy your recently trained model in PyTorch as an API using Python.

  Tags: Data Science Education, Data Scientist, Deep Learning, Flask, Programming, Python, PyTorch

• Xing, Heycar & Microsoft on stage at Deep Learning World in Munich - Mar 19, 2019.
  
  Deep Learning World Munich is coming May 6-7 in Munich, Germany. You still have the chance to get your early bird pass until Apr 5. Secure your ticket for a lower price and access case studies and deep dives covering the commercial deployment of deep learning!

  Tags: Deep Learning, Germany, Microsoft, Munich, PAW, Predictive Analytics World

• How to Train a Keras Model 20x Faster with a TPU for Free - Mar 19, 2019.
  
  This post shows how to train an LSTM Model using Keras and Google CoLaboratory with TPUs to exponentially reduce training time compared to a GPU on your local machine.

  Tags: CoLaboratory, Deep Learning, Keras, Python, TensorFlow, TPU

• Artificial Neural Networks Optimization using Genetic Algorithm with Python - Mar 18, 2019.
  
  This tutorial explains the usage of the genetic algorithm for optimizing the network weights of an Artificial Neural Network for improved performance.

  Pages: 1 2

  Tags: AI, Algorithms, Deep Learning, Machine Learning, Neural Networks, numpy, Optimization, Python

• Deep Learning Summit Boston – Meet RE•WORK’s Newest Speakers - Mar 14, 2019.
  
  RE-WORK returns to Boston in May to showcase global experts in Deep Learning. Get up to 50% off passes with code KDNUGGETS if you register before March 22.

  Tags: Boston, Deep Learning, Healthcare, RE.WORK, Summit

• Top KDnuggets tweets, Mar 06-12: Most impactful AI trends of 2018; Google open-sources GPipe for efficiently training large deep neural networks - Mar 13, 2019.
  
  The rise of ML Engineering; Build your own Robust #DeepLearning Environment in Minutes; Another 10 Free Must-Read Books for Machine Learning and Data Science; Top 5 #MachineLearning Courses for 2019 - from @Coursera and @EdX.

  Tags: Deep Learning, Google, Top tweets

• Towards Automatic Text Summarization: Extractive Methods - Mar 13, 2019.
  
  The basic idea looks simple: find the gist, cut off all opinions and detail, and write a couple of perfect sentences, the task inevitably ended up in toil and turmoil. Here is a short overview of traditional approaches that have beaten a path to advanced deep learning techniques.

  Tags: Bayesian, Deep Learning, Machine Learning, Sciforce, Text Analysis, Text Mining, Topic Modeling

• AI: Arms Race 2.0 - Mar 12, 2019.
  
  An analysis of the current state of the competition between US, Europe, and China in AI, examining research, patent publications, global datasphere, devices and IoT, people, and more.

  Tags: AI, China, Deep Learning, Europe, Investment, IoT, Machine Learning, Neural Networks, startups, Trends, USA

• People Tracking using Deep Learning - Mar 12, 2019.
  
  Read this overview of people tracking and how deep learning-powered computer vision has allowed for phenomenal performance.

  Tags: Deep Learning, Image Recognition, Object Detection

• LiveVideo Courses on AI, Big Data, Machine Learning – only $25 through March 31 - Mar 11, 2019.
  
  All Manning live video courses, includes courses on AI, Big Data, Deep Learning, Machine Learning, Reinforcement Learning, and more - are on sale until March 31 - only twenty five dollars.

  Tags: Big Data, Deep Learning, Manning, Online Education, Reinforcement Learning

• Breaking neural networks with adversarial attacks - Mar 7, 2019.
  
  We develop an intuition behind "adversarial attacks" on deep neural networks, and understand why these attacks are so successful.

  Tags: Adversarial, Deep Learning, Neural Networks, Privacy

• Neural Networks seem to follow a puzzlingly simple strategy to classify images - Mar 5, 2019.
  
  We explain why state-of-the-art Deep Neural Networks can still recognize scrambled images perfectly well and how this helps to uncover a puzzlingly simple strategy that DNNs seem to use to classify natural images.

  Tags: Classification, Deep Learning, Deep Neural Network, ICLR, Image Classification, ImageNet, Neural Networks

• GANs Need Some Attention, Too - Mar 5, 2019.
  
  Self-Attention Generative Adversarial Networks (SAGAN; Zhang et al., 2018) are convolutional neural networks that use the self-attention paradigm to capture long-range spatial relationships in existing images to better synthesize new images.

  Tags: AISC, Attention, Deep Learning, GANs, Image Generation, Machine Learning

• Deep Learning for Natural Language Processing (NLP)  – using RNNs & CNNs - Feb 21, 2019.
  
  We investigate several Natural Language Processing tasks and explain how Deep Learning can help, looking at Language Modeling, Sentiment Analysis, Language Translation, and more.

  Tags: Convolutional Neural Networks, Deep Learning, NLP, Recurrent Neural Networks, Sentiment Analysis

• Artificial Neural Network Implementation using NumPy and Image Classification - Feb 21, 2019.
  
  This tutorial builds artificial neural network in Python using NumPy from scratch in order to do an image classification application for the Fruits360 dataset

  Pages: 1 2

  Tags: Deep Learning, Machine Learning, Neural Networks, numpy, Python

• Top KDnuggets tweets, Feb 13-19: Intro to Scikit Learn: The Gold Standard of Python ML; The Essential Data Science Venn Diagram - Feb 20, 2019.
  
  Also: Cartoon: #MachineLearning Problems in 2118 #ValentinesDay; A must-read tutorial when you are starting your journey with #DeepLearning.

  Tags: Data Science, Deep Learning, scikit-learn, Top tweets, Valentine's Day, Venn Diagram

• Deep Multi-Task Learning – 3 Lessons Learned - Feb 15, 2019.
  
  We share specific points to consider when implementing multi-task learning in a Neural Network (NN) and present TensorFlow solutions to these issues.

  Tags: Deep Learning, Deep Neural Network, Machine Learning, Neural Networks, Optimization, TensorFlow

• Deep Learning World Agenda Now Released! - Feb 13, 2019.
  
  The agenda for Deep Learning World Europe has just been released. Industry leaders will gather in Munich to foster progress in the value-driven operationalization of established deep learning methods. Register now and take advantage of Early Bird rates!

  Tags: Deep Learning, Las Vegas, NV, PAW, Predictive Analytics World

• Trending Deep Learning Github Repositories - Feb 1, 2019.
  
  Check these pair of resources for trending and top GitHub deep learning repositories for some new ideas on what to be looking out for.

  Tags: Deep Learning, GitHub, Trends

• What were the most significant machine learning/AI advances in 2018? - Jan 22, 2019.
  
  2018 was an exciting year for Machine Learning and AI. We saw “smarter” AI, real-world applications, improvements in underlying algorithms and a greater discussion on the impact of AI on human civilization. In this post, we discuss some of the highlights.

  Tags: 2019 Predictions, AI, AlphaZero, BERT, Deep Learning, Machine Learning, NLP, Trends

• First sessions confirmed for PAW Industry 4.0 and DLW Munich 2019 – Super Early Bird rates available until Feb 1st - Jan 14, 2019.
  
  Get your ticket now for PAW Industry 4.0 and DLW Munich, 6-7 May 2019, and enter a world full of Predictive Maintenance, Anomaly Detection, Risk Management, Internet of Things, Deep Learning, Machine Learning & many more related topics!

  Tags: Deep Learning, Germany, Munich, PAW, Predictive Analytics World

• Biggest Deep Learning Summit – Special KDnuggets Offer - Jan 10, 2019.
  
  At RE•WORK, the team are dedicating 2019 to keep up the high-quality events and to bring you the latest innovations & breakthroughs in AI. RE•WORK are offering a huge saving on all summit passes when you register with the discount code NEWYEAR.

  Tags: AI, Boston, CA, Deep Learning, London, MA, RE.WORK, San Francisco, Summit, UK

• [Webinar] Accelerating Machine Learning on Databricks - Jan 9, 2019.
  
  In this webinar, we will cover some of the latest innovations brought into the Databricks Unified Analytics Platform for Machine Learning.

  Tags: Databricks, Deep Learning, Deployment, Machine Learning

• NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing - Jan 8, 2019.
  
  Trying to keep up with advancements at the overlap of neural networks and natural language processing can be troublesome. That's where the today's spotlighted resource comes in.

  Tags: Deep Learning, Neural Networks, NLP

• Manning Countdown to 2019 – Big Deals on AI, Data Science, Machine Learning books and videos - Dec 28, 2018.
  
  Introducing the Manning countdown to 2019, where each day you’ll be able to get a different one day deal on some of their biggest books and video courses.

  Tags: Book, Deep Learning, ebook, Manning, Python

• Supervised Learning: Model Popularity from Past to Present - Dec 28, 2018.
  
  An extensive look at the history of machine learning models, using historical data from the number of publications of each type to attempt to answer the question: what is the most popular model?

  Tags: Decision Trees, Deep Learning, Linear Regression, Logistic Regression, Machine Learning, Neural Networks, Support Vector Machines

• World’s Biggest Deep Learning Summit 3 weeks away - Dec 27, 2018.
  
  RE•WORK will be running a New Year's discount next week, but are offering exclusive early access to KDnuggets subscribers - save 25% when you register with the code NEWYEAR before January 11th.

  Tags: AI, CA, Deep Learning, RE.WORK, San Francisco

• Deep learning in Satellite imagery - Dec 26, 2018.
  
  This article outlines possible sources of satellite imagery, what its properties are and how this data can be utilised using R.

  Tags: Deep Learning, Image Recognition, R

• Interspeech 2018: Highlights for Data Scientists - Dec 24, 2018.
  
  Key highlights from the Interspeech conference, with topics covering end-to-end models for automatic speech recognition, information theory approach to deep learning, speech processing and education, and more.

  Tags: Data Science, Deep Learning, India, Sciforce, Speech, Speech Recognition

• 10 More Must-See Free Courses for Machine Learning and Data Science - Dec 20, 2018.
  
  Have a look at this follow-up collection of free machine learning and data science courses to give you some winter study ideas.

  Tags: AI, Algorithms, Big Data, Data Science, Deep Learning, Machine Learning, MIT, NLP, Reinforcement Learning, U. of Washington, UC Berkeley, Yandex

• Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning - Dec 19, 2018.
  
  Here are the top 15 Python libraries across Data Science, Data Visualization. Deep Learning, and Machine Learning.

  Tags: Data Science, Deep Learning, Machine Learning, Pandas, Python, PyTorch, TensorFlow

• How to do Deep Learning with SAS - Dec 18, 2018.
  
  Build a deep learning model using SAS. This paper offers a how-to guide so that you can get up and running.

  Tags: Deep Learning, SAS

• NLP Breakthrough Imagenet Moment has arrived - Dec 14, 2018.
  
  A comprehensive review of the current state of Natural Language Processing, covering the process from shallow to deep pre-training, what's in an ImageNet, the case for language modelling, and more.

  Tags: Deep Learning, ImageNet, NLP, OpenAI, ULMFiT

• State of Deep Learning and Major Advances: H2 2018 Review - Dec 13, 2018.
  
  In this post we summarise some of the key developments in deep learning in the second half of 2018, before briefly discussing the road ahead for the deep learning community.

  Tags: Deep Learning, Generative Adversarial Network, NLP, PyTorch, TensorFlow, Trends

• A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more - Dec 7, 2018.
  
  A thorough collection of useful resources covering statistics, classic machine learning, deep learning, probability, reinforcement learning, and more.

  Tags: Cheat Sheet, Data Science Education, Deep Learning, Machine Learning, Mathematics, Open Source, Reinforcement Learning, Resources, Statistics

• KDnuggets™ News 18:n46, Dec 5: AI, Data Science, Analytics 2018 Main Developments, 2019 Key Trends; Deep Learning Cheat Sheets - Dec 5, 2018.
  
  Also: Best Machine Learning languages, Data Visualization Tools, DL Frameworks, and Big Data Tools; How to Build a Machine Learning Team When You Are Not Google or Facebook; A Complete Guide to Choosing the Best Machine Learning Course; Handling Imbalanced Datasets in Deep Learning

  Tags: 2019 Predictions, AI, Analytics, Cheat Sheet, Data Science, Deep Learning, Facebook, Google, Machine Learning

• Handling Imbalanced Datasets in Deep Learning - Dec 4, 2018.
  
  It’s important to understand why we should do it so that we can be sure it’s a valuable investment. Class balancing techniques are only really necessary when we actually care about the minority classes.

  Tags: Balancing Classes, Datasets, Deep Learning, Keras, Python

• Upcoming Meetings in AI, Analytics, Big Data, Data Science, Deep Learning, Machine Learning: December and Beyond - Dec 3, 2018.
  
  Coming soon: DataX New York, AI-2018 Cambridge UK, AI NEXTCon Seattle, Deep Learning Summit San Francisco, EGC France, H2O San Francisco, Business Of Bots Business of Bots San Francisco, TDWI Las Vegas, WSDM Melbourne, and more.

  Tags: AI, Analytics, Big Data, Boston, Data Science, Deep Learning, Las Vegas, London, Meetings, New York City, San Francisco

• Best Machine Learning Languages, Data Visualization Tools, DL Frameworks, and Big Data Tools - Dec 3, 2018.
  
  We cover a variety of topics, from machine learning to deep learning, from data visualization to data tools, with comments and explanations from experts in the relevant fields.

  Tags: Big Data, Data Visualization, Deep Learning, Jupyter, Machine Learning, Python, R, Tableau

• Deep Learning for the Masses (… and The Semantic Layer) - Nov 30, 2018.
  
  Deep learning is everywhere right now, in your watch, in your television, your phone, and in someway the platform you are using to read this article. Here I’ll talk about how can you start changing your business using Deep Learning in a very simple way. But first, you need to know about the Semantic Layer.

  Pages: 1 2

  Tags: AI, Deep Learning, Machine Learning, Semantic Analysis

• Variational Autoencoders Explained in Detail - Nov 30, 2018.
  
  We explain how to implement VAE - including simple to understand tensorflow code using MNIST and a cool trick of how you can generate an image of a digit conditioned on the digit.

  Tags: Autoencoder, Deep Learning, Machine Learning, MNIST, TensorFlow

• Deep Learning Cheat Sheets - Nov 28, 2018.
  
  Check out this collection of high-quality deep learning cheat sheets, filled with valuable, concise information on a variety of neural network-related topics.

  Tags: Cheat Sheet, Deep Learning, Neural Networks

• How to Engineer Your Way Out of Slow Models - Nov 27, 2018.
  
  We describe how we handle performance issues with our deep learning models, including how to find subgraphs that take a lot of calculation time and how to extract these into a caching mechanism.

  Tags: Deep Learning, Scalability

• Join the World’s Biggest Deep Learning Summit – KDnuggets Early Cyber Monday - Nov 21, 2018.
  
  RE•WORK are offering an exclusive early discount to KDnuggets subscribers for any of their upcoming AI and Deep Learning Summits when you register before November 30th with the code CYBER25.

  Tags: AI, Boston, CA, Deep Learning, Houston, London, MA, RE.WORK, San Francisco, Summit, TX, UK

• Best Deals in Deep Learning Cloud Providers: From CPU to GPU to TPU - Nov 15, 2018.
  
  A detailed comparison of the best places to train your deep learning model for the lowest cost and hassle, including AWS, Google, Paperspace, vast.ai, and more.

  Tags: Cloud Computing, Deep Learning, GPU, TPU

• Deep Learning Performance Cheat Sheet - Nov 8, 2018.
  
  We outline a variety of simple and complex tricks that can help you boost your deep learning models accuracy, from basic optimization, to open source labeling software.

  Tags: Cheat Sheet, Deep Learning, Performance

• 10 Free Must-See Courses for Machine Learning and Data Science - Nov 8, 2018.
  
  Check out a collection of free machine learning and data science courses to kick off your winter learning season.

  Tags: Data Science, Deep Learning, fast.ai, Google, Linear Algebra, Machine Learning, MIT, NLP, Reinforcement Learning, Stanford, Yandex

• Introduction to PyTorch for Deep Learning - Nov 7, 2018.
  
  In this tutorial, you’ll get an introduction to deep learning using the PyTorch framework, and by its conclusion, you’ll be comfortable applying it to your deep learning models.

  Tags: Deep Learning, Neural Networks, Python, PyTorch

• KDnuggets™ News 18:n42, Nov 7: The Most in Demand Skills for Data Scientists; How Machines Understand Our Language: Intro to NLP - Nov 7, 2018.
  
  Also: Machine Learning Classification: A Dataset-based Pictorial; Quantum Machine Learning: A look at myths, realities, and future projections; Multi-Class Text Classification Model Comparison and Selection; Top 13 Python Deep Learning Libraries

  Tags: Classification, Data Science Skills, Deep Learning, Myths, NLP, Python, Text Classification

• Top 13 Python Deep Learning Libraries - Nov 2, 2018.
  
  Part 2 of a new series investigating the top Python Libraries across Machine Learning, AI, Deep Learning and Data Science.

  Tags: Caffe, Deep Learning, GitHub, MXNet, Python, PyTorch, TensorFlow, Theano

• Upcoming Meetings in AI, Analytics, Big Data, Data Science, Deep Learning, Machine Learning: November and Beyond - Nov 1, 2018.
  
  Coming soon: PASS Summit Seattle, TDWI Orlando, IEEE Conf on Data Mining Singapore, AI & Big Data Innovation Summit 2018 Beijing, Deep Learning World Berlin, PAW Business Berlin, Big Data LDN London, NIPS, and many more.

  Tags: AI, Analytics, Big Data, Boston, Deep Learning, London, Meetings, New York City, San Francisco

• Join AI experts from Google Brain, Open AI & Uber AI Labs in San Francisco - Nov 1, 2018.
  
  Join us at the Deep Learning Summit, San Francisco, 24 - 25 Jan 2019. Learn from industry experts in speech & pattern recognition, neural networks, image analysis and NLP, and explore how deep learning will impact all industries.

  Tags: AI, CA, Deep Learning, Google, OpenAI, RE.WORK, San Francisco, Uber

• KDnuggets™ News 18:n41, Oct 31: Introduction to Deep Learning with Keras; Easy Named Entity Recognition with Scikit-Learn - Oct 31, 2018.
  
  Also: Generative Adversarial Networks - Paper Reading Road Map; How I Learned to Stop Worrying and Love Uncertainty; Implementing Automated Machine Learning Systems with Open Source Tools; Notes on Feature Preprocessing: The What, the Why, and the How

  Tags: Automated Machine Learning, Data Preprocessing, Deep Learning, Generative Adversarial Network, Keras, NLP, Python, scikit-learn

• Introduction to Deep Learning with Keras - Oct 29, 2018.
  
  In this article, we’ll build a simple neural network using Keras. Now let’s proceed to solve a real business problem: an insurance company wants you to develop a model to help them predict which claims look fraudulent.

  Pages: 1 2

  Tags: Deep Learning, Keras, Neural Networks, Python

• A Deep Look at Deep Learning: Understanding The Basics of How (and Why) it Works - Oct 23, 2018.
  
  In this illustrated guide by Dataiku you'll learn what exactly deep learning is and why its growing and why it can be more powerful than classical machine learning (ML).

  Tags: Dataiku, Deep Learning, Machine Learning

• Google, Microsoft & Fraunhofer at the First European Edition of Deep Learning World – 12 Nov, 2018 - Oct 23, 2018.
  
  You can attend the premier conference covering the commercial deployment of Deep Learning, Nov 12, Berlin, and learn from top industry experts, from our first class conference programme, and from reputable companies to become the best in what you're doing!

  Tags: Berlin, Deep Learning, Germany, PAW, Predictive Analytics World

• Speak at Mega-PAW Vegas 2019 – on Machine Learning Deployment (Apply by Nov 15) - Oct 22, 2018.
  
  Presenting at PAW is a fulfilling way to engage with the leading members of the machine learning community, offers a chance to share how predictive analytics delivers an impact for your organization, and provides complimentary registration/access to the PAW event.

  Tags: Deep Learning, Las Vegas, Machine Learning, NV, PAW, Predictive Analytics World

• Adversarial Examples, Explained - Oct 16, 2018.
  
  Deep neural networks—the kind of machine learning models that have recently led to dramatic performance improvements in a wide range of applications—are vulnerable to tiny perturbations of their inputs. We investigate how to deal with these vulnerabilities.

  Tags: Adversarial, Deep Learning

• Preprocessing for Deep Learning: From covariance matrix to image whitening - Oct 10, 2018.
  
  The goal of this post/notebook is to go from the basics of data preprocessing to modern techniques used in deep learning. My point is that we can use code (Python/Numpy etc.) to better understand abstract mathematical notions!

  Pages: 1 2 3

  Tags: Data Preprocessing, Deep Learning, Image Processing, Mathematics

• KDnuggets™ News 18:n38, Oct 10: Concise Explanation of Learning Algorithms; Why I Call Myself a Data Scientist; Linear Regression in the Wild - Oct 10, 2018.
  
  This week, KDnuggets brings you a discussion of learning algorithms with a hat tip to Tom Mitchell, discusses why you might call yourself a data scientist, explores machine learning in the wild, checks out some top trends in deep learning, shows you how to learn data science if you are low on finances, and puts forth one person's opinion on the top 8 Python machine learning libraries to help get the job done.

  Tags: Algorithms, Data Science, Deep Learning, Linear Regression, Machine Learning, Python, Tom Mitchell

• Big Data Day Camp: Big Data Tools & Techniques (October 25-26) - Oct 4, 2018.
  
  Learn how to use data to make wise, actionable data driven decisions! Our first 2-day camp, Big Data Tools & Techniques, is October 25-26 at Qualcomm Institute, UCSD.

  Tags: Apache Spark, Big Data, Deep Learning, Hadoop, Kafka

• Semantic Segmentation: Wiki, Applications and Resources - Oct 4, 2018.
  
  An extensive overview covering the features of Semantic Segmentation and possible uses for it, including GeoSensing, Autonomous Drive, Facial Recognition and more.

  Tags: Deep Learning, Image Recognition, Machine Learning, Object Detection, Segmentation

• Top 3 Trends in Deep Learning - Oct 3, 2018.
  
  We investigate the intermediate stage of deep learning, and the trends that are emerging in response to the challenges at this stage, including Interoperability and the multi-deployment options.

  Tags: Cloud Computing, Deep Learning, MathWorks

• KDnuggets™ News 18:n37, Oct 3: Mathematics of Machine Learning; Effective Transfer Learning for NLP; Path Analysis with R - Oct 3, 2018.
  
  Also: Introducing VisualData: A Search Engine for Computer Vision Datasets; Raspberry Pi IoT Projects for Fun and Profit; Recent Advances for a Better Understanding of Deep Learning; Basic Image Data Analysis Using Python - Part 3; Introduction to Deep Learning

  Tags: Computer Vision, Deep Learning, Machine Learning, Mathematics, NLP, R, Transfer Learning

• Recent Advances for a Better Understanding of Deep Learning - Oct 1, 2018.
  
  A summary of the newest deep learning trends, including Non Convex Optimization, Overparametrization and Generalization, Generative Models, Stochastic Gradient Descent (SGD) and more.

  Tags: Deep Learning, Explained, Flat Minima, Linear Networks, Machine Learning, Optimization, SGD

• Join us in Toronto for the Deep Learning Summit, Save with KDnuggets - Sep 28, 2018.
  
  RE•WORK's world-famous Deep Learning Summit is taking place in Toronto this October with the addition of a new AI for Government track. Don't forget to use code KDNUGGETS at the checkout for 20% off your pass. See you there!

  Tags: AI, Canada, Deep Learning, Government, RE.WORK, Toronto

• Introduction to Deep Learning - Sep 28, 2018.
  
  I decided to begin to put some structure in my understanding of Neural Networks through this series of articles.

  Tags: Beginners, Deep Learning, Neural Networks

• ODSC India Highlights: Deep Learning Revolution in Speech, AI Engineer vs Data Scientist, and Reinforcement Learning for Enterprise - Sep 26, 2018.
  
  Key takeaways and highlights from ODSC India 2018 conference about the latest trends, breakthroughs and revolutions in the field of Data Science and Artificial Intelligence

  Tags: AI, Chatbot, Deep Learning, Machine Learning, NLP, ODSC, Recurrent Neural Networks, Reinforcement Learning, Speech Recognition

• Power Laws in Deep Learning 2: Universality - Sep 26, 2018.
  
  It is amazing that Deep Neural Networks display this Universality in their weight matrices, and this suggests some deeper reason for Why Deep Learning Works.

  Tags: Deep Learning, Explained, Neural Networks

• KDnuggets™ News 18:n36, Sep 26: Machine Learning Algorithms From Scratch; Deep Learning Framework Popularity; Data Capture, the Deep Learning Way - Sep 26, 2018.
  
  Also: SQL Case Study: Helping a Startup CEO Manage His Data; Building a Machine Learning Model through Trial and Error; The Whys and Hows of Web Scraping; Unfolding Naive Bayes From Scratch; "Auto-What?" -  A Taxonomy of Automated Machine Learning

  Tags: Algorithms, Automated Machine Learning, Deep Learning, Machine Learning, Perceptron, SQL, Web Scraping