Search results for Convolutional Neural Network

Found 432 documents, 5946 searched:

• HuggingFace Has Launched a Free Deep Reinforcement Learning Course

  Hugging Face has released a free course on Deep RL. It is self-paced and shares a lot of pointers on theory, tutorials, and hands-on guides.

  https://www.kdnuggets.com/2022/05/huggingface-launched-free-deep-reinforcement-learning-course.html

• A Brief Introduction to Papers With Code

  One-stop shop to learn about state-of-the-art research papers with access to open-source resources including machine learning models, datasets, methods, evaluation tables, and code.

  https://www.kdnuggets.com/2022/04/brief-introduction-papers-code.html

• Uncertainty Quantification in Artificial Intelligence-based Systems

  The article summarizes the plethora of UQ methods using Bayesian techniques, shows issues and gaps in the literature, suggests further directions, and epitomizes AI-based systems within the Financial Crime domain.

  https://www.kdnuggets.com/2022/04/uncertainty-quantification-artificial-intelligencebased-systems.html

• Classifying Long Text Documents Using BERT

  Transformer based language models such as BERT are really good at understanding the semantic context because they were designed specifically for that purpose. BERT outperforms all NLP baselines, but as we say in the scientific community, “no free lunch”. How can we use BERT to classify long text documents?

  https://www.kdnuggets.com/2022/02/classifying-long-text-documents-bert.html

• 6 Predictive Models Every Beginner Data Scientist Should Master">6 Predictive Models Every Beginner Data Scientist Should Master

  Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.

  https://www.kdnuggets.com/2021/12/6-predictive-models-every-beginner-data-scientist-master.html

• 10 Key AI & Data Analytics Trends for 2022 and Beyond

  What AI and data analytics trends are taking the industry by storm this year? This comprehensive review highlights upcoming directions in AI to carefully watch and consider implementing in your personal work or organization.

  https://www.kdnuggets.com/2021/12/10-key-ai-trends-for-2022.html

• Main 2021 Developments and Key 2022 Trends in AI, Data Science, Machine Learning Technology

  Our panel of leading experts reviews 2021 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.

  https://www.kdnuggets.com/2021/12/trends-ai-data-science-ml-technology.html

• 10 AI Project Ideas in Computer Vision

  The field of computer vision has seen the development of very powerful applications leveraging machine learning. These projects will introduce you to these techniques and guide you to more advanced practice to gain a deeper appreciation for the sophistication now available.

  https://www.kdnuggets.com/2021/11/10-ai-project-ideas-computer-vision.html

• Machine Learning Model Development and Model Operations: Principles and Practices">Machine Learning Model Development and Model Operations: Principles and Practices

  The ML model management and the delivery of highly performing model is as important as the initial build of the model by choosing right dataset. The concepts around model retraining, model versioning, model deployment and model monitoring are the basis for machine learning operations (MLOps) that helps the data science teams deliver highly performing models.

  https://www.kdnuggets.com/2021/10/machine-learning-model-development-operations-principles-practice.html

• How to Create an Interactive Dashboard in Three Steps with KNIME Analytics Platform

  In this blog post I will show you how to build a simple, but useful and good-looking dashboard to present your data - in three simple steps!

  https://www.kdnuggets.com/2021/10/interactive-dashboard-three-steps-knime-analytics-platform.html

• Computer Vision in Agriculture

  Deep learning isn’t just for placing ads or identifying cats anymore. Instead, a slew of young startups have started to incorporate the advances in computer vision made possible through larger and larger neural networks to real working robots in the fields.

  https://www.kdnuggets.com/2021/09/computer-vision-agriculture.html

• Path to Full Stack Data Science">Path to Full Stack Data Science

  Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.

  https://www.kdnuggets.com/2021/09/path-full-stack-data-science.html

• 20 Machine Learning Projects That Will Get You Hired">20 Machine Learning Projects That Will Get You Hired

  If you want to break into the machine learning and data science job market, then you will need to demonstrate the proficiency of your skills, especially if you are self-taught through online courses and bootcamps. A project portfolio is a great way to practice your new craft and offer convincing evidence that an employee should hire you over the competition.

  https://www.kdnuggets.com/2021/09/20-machine-learning-projects-hired.html

• 8 Deep Learning Project Ideas for Beginners">8 Deep Learning Project Ideas for Beginners

  Have you studied Deep Learning techniques, but never worked on a useful project? Here, we highlight eight deep learning project ideas for beginners that will help you sharpen your skills and boost your resume.

  https://www.kdnuggets.com/2021/09/8-deep-learning-project-ideas-beginners.html

• Machine Learning Skills – Update Yours This Summer

  The process of mastering new knowledge often requires multiple passes to ensure the information is deeply understood. If you already began your journey into machine learning and data science, then you are likely ready for a refresher on topics you previously covered. This eight-week self-learning path will help you recapture the foundations and prepare you for future success in applying these skills.

  https://www.kdnuggets.com/2021/07/update-your-machine-learning-skills.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 5

  Training efficient deep learning models with any software tool is nothing without an infrastructure of robust and performant compute power. Here, current software and hardware ecosystems are reviewed that you might consider in your development when the highest performance possible is needed.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part5.html

• 7 Open Source Libraries for Deep Learning Graphs

  In this article we’ll go through 7 up-and-coming open source libraries for graph deep learning, ranked in order of increasing popularity.

  https://www.kdnuggets.com/2021/07/7-open-source-libraries-deep-learning-graphs.html

• Exploring the SwAV Method

  This post discusses the SwAV (Swapping Assignments between multiple Views of the same image) method from the paper “Unsupervised Learning of Visual Features by Contrasting Cluster Assignments” by M. Caron et al.

  https://www.kdnuggets.com/2021/07/swav-method.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 3

  Now that you are ready to efficiently build advanced deep learning models with the right software and hardware tools, the techniques involved in implementing such efforts must be explored to improve model quality and obtain the performance that your organization desires.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part3.html

• Computational Complexity of Deep Learning: Solution Approaches

  Why has deep learning been so successful? What is the fundamental reason that deep learning can learn from big data? Why cannot traditional ML learn from the large data sets that are now available for different tasks as efficiently as deep learning can?

  https://www.kdnuggets.com/2021/06/computational-complexity-deep-learning-solution-approaches.html

• High Performance Deep Learning, Part 1

  Advancing deep learning techniques continue to demonstrate incredible potential to deliver exciting new AI-enhanced software and systems. But, training the most powerful models is expensive--financially, computationally, and environmentally. Increasing the efficiency of such models will have profound impacts in many ways, so developing future models with this intension in mind will only help to further expand the reach, applicability, and value of what deep learning has to offer.

  https://www.kdnuggets.com/2021/06/efficiency-deep-learning-part1.html

• Beginners Guide to Debugging TensorFlow Models

  If you are new to working with a deep learning framework, such as TensorFlow, there are a variety of typical errors beginners face when building and training models. Here, we explore and solve some of the most common errors to help you develop a better intuition for debugging in TensorFlow.

  https://www.kdnuggets.com/2021/06/beginners-guide-debugging-tensorflow-models.html

• A checklist to track your Data Science progress">A checklist to track your Data Science progress

  Whether you are just starting out in data science or already a gainfully-employed professional, always learning more to advance through state-of-the-art techniques is part of the adventure. But, it can be challenging to track of your progress and keep an eye on what's next. Follow this checklist to help you scale your expertise from entry-level to advanced.

  https://www.kdnuggets.com/2021/05/checklist-data-science-progress.html

• The Three Edge Case Culprits: Bias, Variance, and Unpredictability

  Edge cases occur for three basic reasons: Bias – the ML system is too ‘simple’; Variance – the ML system is too ‘inexperienced’; Unpredictability – the ML system operates in an environment full of surprises. How do we recognize these edge cases situations, and what can we do about them?

  https://www.kdnuggets.com/2021/04/imerit2-bias-variance-unpredictability.html

• How Noisy Labels Impact Machine Learning Models

  Not all training data labeling errors have the same impact on the performance of the Machine Learning system. The structure of the labeling errors make a difference. Read iMerit’s latest blog to learn how to minimize the impact of labeling errors.

  https://www.kdnuggets.com/2021/04/imerit-noisy-labels-impact-machine-learning.html

• DeepMind’s AlphaFold & the Protein Folding Problem

  Recently, DeepMind's AlphaFold made impressive headway in the protein structure prediction problem. Read this for an overview and explanation.

  https://www.kdnuggets.com/2021/03/deepmind-alphafold-protein-folding-problem.html

• Deep learning doesn’t need to be a black box">Deep learning doesn’t need to be a black box

  The cultural perception of AI is often suspect because of the described challenges in knowing why a deep neural network makes its predictions. So, researchers try to crack open this "black box" after a network is trained to correlate results with inputs. But, what if the goal of explainability could be designed into the network's architecture -- before the model is trained and without reducing its predictive power? Maybe the box could stay open from the beginning.

  https://www.kdnuggets.com/2021/02/deep-learning-not-black-box.html

• Vision Transformers: Natural Language Processing (NLP) Increases Efficiency and Model Generality

  Why do we hear so little about transformer models applied to computer vision tasks? What about attention in computer vision networks?

  https://www.kdnuggets.com/2021/02/vision-transformers-nlp-efficiency-model-generality.html

• Machine learning adversarial attacks are a ticking time bomb

  Software developers and cyber security experts have long fought the good fight against vulnerabilities in code to defend against hackers. A new, subtle approach to maliciously targeting machine learning models has been a recent hot topic in research, but its statistical nature makes it difficult to find and patch these so-called adversarial attacks. Such threats in the real-world are becoming imminent as the adoption of machine learning spreads, and a systematic defense must be implemented.

  https://www.kdnuggets.com/2021/01/machine-learning-adversarial-attacks.html

• Support Vector Machine for Hand Written Alphabet Recognition in R

  We attempt to break down a problem of hand written alphabet image recognition into a simple process rather than using heavy packages. This is an attempt to create the data and then build a model using Support Vector Machines for Classification.

  https://www.kdnuggets.com/2021/01/support-vector-machine-hand-written-alphabet-r.html

• Deep Learning Pioneer Geoff Hinton on his Latest Research and the Future of AI

  Geoff Hinton has lived at the outer reaches of machine learning research since an aborted attempt at a carpentry career a half century ago. He spoke to Craig Smith about his work In 2020 and what he sees on the horizon for AI.

  https://www.kdnuggets.com/2021/01/deep-learning-pioneer-geoff-hinton-research-future-ai.html

• Mastering TensorFlow Variables in 5 Easy Steps

  Learn how to use TensorFlow Variables, their differences from plain Tensor objects, and when they are preferred over these Tensor objects | Deep Learning with TensorFlow 2.x.

  https://www.kdnuggets.com/2021/01/mastering-tensorflow-variables-5-easy-steps.html

• 2020: A Year Full of Amazing AI Papers — A Review

  So much happened in the world during 2020 that it may have been easy to miss the great progress in the world of AI. To catch you up quickly, check out this curated list of the latest breakthroughs in AI by release date, along with a video explanation, link to an in-depth article, and code.

  https://www.kdnuggets.com/2020/12/2020-amazing-ai-papers.html

• Covid or just a Cough? AI for detecting COVID-19 from Cough Sounds

  Increased capabilities in screening and early testing for a disease can significantly support quelling its spread and impact. Recent progress in developing deep learning AI models to classify cough sounds as a prescreening tool for COVID-19 has demonstrated promising early success. Cough-based diagnosis is non-invasive, cost-effective, scalable, and, if approved, could be a potential game-changer in our fight against COVID-19.

  https://www.kdnuggets.com/2020/12/covid-cough-ai-detecting-sounds.html

• State of Data Science and Machine Learning 2020: 3 Key Findings">State of Data Science and Machine Learning 2020: 3 Key Findings

  Kaggle recently released its State of Data Science and Machine Learning report for 2020, based on compiled results of its annual survey. Read about 3 key findings in the report here.

  https://www.kdnuggets.com/2020/12/kaggle-survey-2020-data-science-machine-learning.html

• Mastering TensorFlow Tensors in 5 Easy Steps

  Discover how the building blocks of TensorFlow works at the lower level and learn how to make the most of Tensor objects.

  https://www.kdnuggets.com/2020/11/mastering-tensorflow-tensors-5-easy-steps.html

• My Data Science Online Learning Journey on Coursera

  Check out the author's informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey.

  https://www.kdnuggets.com/2020/11/data-science-online-learning-journey-coursera.html

• Doing the impossible? Machine learning with less than one example

  Machine learning algorithms are notoriously known for needing data, a lot of data -- the more data the better. But, much research has gone into developing new methods that need fewer examples to train a model, such as "few-shot" or "one-shot" learning that require only a handful or a few as one example for effective learning. Now, this lower boundary on training examples is being taken to the next extreme.

  https://www.kdnuggets.com/2020/11/machine-learning-less-than-one-example.html

• Interpretability, Explainability, and Machine Learning – What Data Scientists Need to Know

  The terms “interpretability,” “explainability” and “black box” are tossed about a lot in the context of machine learning, but what do they really mean, and why do they matter?

  https://www.kdnuggets.com/2020/11/interpretability-explainability-machine-learning.html

• Building Deep Learning Projects with fastai — From Model Training to Deployment

  A getting started guide to develop computer vision application with fastai.

  https://www.kdnuggets.com/2020/11/building-deep-learning-projects-fastai-model-training-deployment.html

• Explaining the Explainable AI: A 2-Stage Approach

  Understanding how to build AI models is one thing. Understanding why AI models provide the results they provide is another. Even more so, explaining any type of understanding of AI models to humans is yet another challenging layer that must be addressed if we are to develop a complete approach to Explainable AI.

  https://www.kdnuggets.com/2020/10/explaining-explainable-ai.html

• An Introduction to AI, updated">An Introduction to AI, updated

  We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.

  https://www.kdnuggets.com/2020/10/introduction-ai-updated.html

• Roadmap to Computer Vision

  Read this introduction to the main steps which compose a computer vision system, starting from how images are pre-processed, features extracted and predictions are made.

  https://www.kdnuggets.com/2020/10/roadmap-computer-vision.html

• Behavior Analysis with Machine Learning and R: The free eBook

  Check out this new free ebook to learn how to leverage the power of machine learning to analyze behavioral patterns from sensor data and electronic records using R.

  https://www.kdnuggets.com/2020/10/behavior-analysis-machine-learning-r-free-ebook.html

• Artificial Intelligence for Precision Medicine and Better Healthcare

  In this article, we will focus on various machine learning, deep learning models, and applications of AI which can pave the way for a new data-centric era of discovery in healthcare.

  https://www.kdnuggets.com/2020/09/artificial-intelligence-precision-medicine-better-healthcare.html

• MathWorks Deep learning workflow: tips, tricks, and often forgotten steps

  Getting started in deep learning – and adopting an organized, sustainable, and reproducible workflow – can be challenging. This blog post will share some tips and tricks to help you develop a systematic, effective, attainable, and scalable deep learning workflow as you experiment with different deep learning models, datasets, and applications.

  https://www.kdnuggets.com/2020/09/mathworks-deep-learning-workflow.html

• Deep Learning’s Most Important Ideas">Deep Learning’s Most Important Ideas

  In the field of deep learning, there continues to be a deluge of research and new papers published daily. Many well-adopted ideas that have stood the test of time provide the foundation for much of this new work. To better understand modern deep learning, these techniques cover the basic necessary knowledge, especially as a starting point if you are new to the field.

  https://www.kdnuggets.com/2020/09/deep-learnings-most-important-ideas.html

• AI Papers to Read in 2020

  Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.

  https://www.kdnuggets.com/2020/09/ai-papers-read-2020.html

• 8 AI/Machine Learning Projects To Make Your Portfolio Stand Out">8 AI/Machine Learning Projects To Make Your Portfolio Stand Out

  If you are just starting down a path toward a career in Data Science, or you are already a seasoned practitioner, then keeping active to advance your experience through side projects is invaluable to take you to the next professional level. These eight interesting project ideas with source code and reference articles will jump start you to thinking outside of the box.

  https://www.kdnuggets.com/2020/09/8-ml-ai-projects-stand-out.html

• Accelerated Computer Vision: A Free Course From Amazon

  Amazon's Machine Learning University is making its online courses available to the public, and this time we look at its Accelerated Computer Vision offering.

  https://www.kdnuggets.com/2020/08/accelerated-computer-vision-free-course-amazon.html

• Breaking Privacy in Federated Learning

  Despite the benefits of federated learning, there are still ways of breaching a user’s privacy, even without sharing private data. In this article, we’ll review some research papers that discuss how federated learning includes this vulnerability.

  https://www.kdnuggets.com/2020/08/breaking-privacy-federated-learning.html

• A Deep Dive Into the Transformer Architecture – The Development of Transformer Models

  Even though transformers for NLP were introduced only a few years ago, they have delivered major impacts to a variety of fields from reinforcement learning to chemistry. Now is the time to better understand the inner workings of transformer architectures to give you the intuition you need to effectively work with these powerful tools.

  https://www.kdnuggets.com/2020/08/transformer-architecture-development-transformer-models.html

• Must-read NLP and Deep Learning articles for Data Scientists">Must-read NLP and Deep Learning articles for Data Scientists

  NLP and deep learning continue to advance, nearly on a daily basis. Check out these recent must-read guides, feature articles, and other resources to keep you on top of the latest advancements and ahead of the curve.

  https://www.kdnuggets.com/2020/08/must-read-nlp-deep-learning-articles.html

• 3D Human Pose Estimation Experiments and Analysis

  In this article, we explore how 3D human pose estimation works based on our research and experiments, which were part of the analysis of applying human pose estimation in AI fitness coach applications.

  https://www.kdnuggets.com/2020/08/3d-human-pose-estimation-experiments-analysis.html

• Metrics to Use to Evaluate Deep Learning Object Detectors

  It's important to understand which metric should be used to evaluate trained object detectors and which one is more important. Is mAP alone enough to evaluate the objector models? Can the same metric be used to evaluate object detectors on validation set and test set?

  https://www.kdnuggets.com/2020/08/metrics-evaluate-deep-learning-object-detectors.html

• Awesome Machine Learning and AI Courses">Awesome Machine Learning and AI Courses

  Check out this list of awesome, free machine learning and artificial intelligence courses with video lectures.

  https://www.kdnuggets.com/2020/07/awesome-machine-learning-ai-courses.html

• 5 Fantastic Natural Language Processing Books

  This curated collection of 5 natural language processing books attempts to cover a number of different aspects of the field, balancing the practical and the theoretical. Check out these 5 fantastic selections now in order to improve your NLP skills.

  https://www.kdnuggets.com/2020/07/5-fantastic-nlp-books.html

• Labelling Data Using Snorkel

  In this tutorial, we walk through the process of using Snorkel to generate labels for an unlabelled dataset. We will provide you examples of basic Snorkel components by guiding you through a real clinical application of Snorkel.

  https://www.kdnuggets.com/2020/07/labelling-data-using-snorkel.html

• Graph Machine Learning in Genomic Prediction

  This work explores how genetic relationships can be exploited alongside genomic information to predict genetic traits with the aid of graph machine learning algorithms.

  https://www.kdnuggets.com/2020/06/graph-machine-learning-genomic-prediction.html

• Build Dog Breeds Classifier Step By Step with AWS Sagemaker

  This post takes you through the basic steps for creating a cloud-based deep learning dog classifier, with everything accomplished from the AWS Management Console.

  https://www.kdnuggets.com/2020/06/build-dog-breeds-classifier-aws-sagemaker.html

• Crop Disease Detection Using Machine Learning and Computer Vision

  Computer vision has tremendous promise for improving crop monitoring at scale. We present our learnings from building such models for detecting stem and wheat rust in crops.

  https://www.kdnuggets.com/2020/06/crop-disease-detection-computer-vision.html

• Best Machine Learning Youtube Videos Under 10 Minutes

  The Youtube videos on this list cover concepts such as what machine learning is, the basics of natural language processing, how computer vision works, and machine learning in video games.

  https://www.kdnuggets.com/2020/06/best-machine-learning-youtube-videos-under-10-minutes.html

• Deep Learning for Detecting Pneumonia from X-ray Images">Deep Learning for Detecting Pneumonia from X-ray Images

  This article covers an end to end pipeline for pneumonia detection from X-ray images.

  https://www.kdnuggets.com/2020/06/deep-learning-detecting-pneumonia-x-ray-images.html

• Deep Learning for Coders with fastai and PyTorch: The Free eBook">Deep Learning for Coders with fastai and PyTorch: The Free eBook

  If you are interested in a top-down, example-driven book on deep learning, check out the draft of the upcoming Deep Learning for Coders with fastai & PyTorch from fast.ai team.

  https://www.kdnuggets.com/2020/06/fastai-book-free-ebook.html

• 5 Machine Learning Papers on Face Recognition

  This article will highlight some of that research and introduce five machine learning papers on face recognition.

  https://www.kdnuggets.com/2020/05/5-machine-learning-papers-face-recognition.html

• 13 must-read papers from AI experts">13 must-read papers from AI experts

  What research articles do top AI experts in the field recommend? Find out which ones and why, then be sure to add each to your reading to do list.

  https://www.kdnuggets.com/2020/05/13-must-read-papers-ai-experts.html

• What You Need to Know About Deep Reinforcement Learning

  How does deep learning solve the challenges of scale and complexity in reinforcement learning? Learn how combining these approaches will make more progress toward the notion of Artificial General Intelligence.

  https://www.kdnuggets.com/2020/05/deep-reinforcement-learning.html

• Start Your Machine Learning Career in Quarantine">Start Your Machine Learning Career in Quarantine

  While this quarantine can last two months, make the most of it by starting your career in Machine Learning with this 60-day learning plan.

  https://www.kdnuggets.com/2020/05/machine-learning-career-quarantine.html

• Beginners Learning Path for Machine Learning">Beginners Learning Path for Machine Learning

  So, you are interested in machine learning? Here is your complete learning path to start your career in the field.

  https://www.kdnuggets.com/2020/05/beginners-learning-path-machine-learning.html

• Google Open Sources SimCLR, A Framework for Self-Supervised and Semi-Supervised Image Training

  The new framework uses contrastive learning to improve image analysis in unlabeled datasets.

  https://www.kdnuggets.com/2020/04/google-open-sources-simclr-self-supervised-semi-supervised-image-training.html

• 5 Papers on CNNs Every Data Scientist Should Read">5 Papers on CNNs Every Data Scientist Should Read

  In this article, we introduce 5 papers on CNNs that represent both novel approaches and baselines in the field.

  https://www.kdnuggets.com/2020/04/5-papers-cnns-data-scientist.html

• Dive Into Deep Learning: The Free eBook

  This freely available text on deep learning is fully interactive and incredibly thorough. Check out "Dive Into Deep Learning" now and increase your neural networks theoretical understanding and practical implementation skills.

  https://www.kdnuggets.com/2020/04/dive-deep-learning-book.html

• How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals">How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals

  The goal of this essay is to discuss meaningful machine learning progress in the real-world application of drug discovery. There’s even a solid chance of the deep learning approach to drug discovery changing lives for the better doing meaningful good in the world.

  https://www.kdnuggets.com/2020/04/deep-learning-accelerating-drug-discovery-pharmaceuticals.html

• 10 Must-read Machine Learning Articles (March 2020)">10 Must-read Machine Learning Articles (March 2020)

  This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.

  https://www.kdnuggets.com/2020/04/10-must-read-machine-learning-articles-march-2020.html

• Brain Tumor Detection using Mask R-CNN

  Mask R-CNN has been the new state of the art in terms of instance segmentation. Here I want to share some simple understanding of it to give you a first look and then we can move ahead and build our model.

  https://www.kdnuggets.com/2020/03/brain-tumor-detection-mask-r-cnn.html

• Few-Shot Image Classification with Meta-Learning

  Here is how you can teach your model to learn quickly from a few examples.

  https://www.kdnuggets.com/2020/03/few-shot-image-classification-meta-learning.html

• Software Interfaces for Machine Learning Deployment

  While building a machine learning model might be the fun part, it won't do much for anyone else unless it can be deployed into a production environment. How to implement machine learning deployments is a special challenge with differences from traditional software engineering, and this post examines a fundamental first step -- how to create software interfaces so you can develop deployments that are automated and repeatable.

  https://www.kdnuggets.com/2020/03/software-interfaces-machine-learning-deployment.html

• 21 Machine Learning Projects – Datasets Included

  Upgrading your machine learning, AI, and Data Science skills requires practice. To practice, you need to develop models with a large amount of data. Finding good datasets to work with can be challenging, so this article discusses more than 20 great datasets along with machine learning project ideas for you to tackle today.

  https://www.kdnuggets.com/2020/03/20-machine-learning-datasets-project-ideas.html

• Phishytics – Machine Learning for Detecting Phishing Websites

  Since phishing is such a widespread problem in the cybersecurity domain, let us take a look at the application of machine learning for phishing website detection.

  https://www.kdnuggets.com/2020/03/phishytics-machine-learning-detecting-phishing-websites.html

• Hands on Hyperparameter Tuning with Keras Tuner

  Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%.

  https://www.kdnuggets.com/2020/02/hyperparameter-tuning-keras-tuner.html

• Audio Data Analysis Using Deep Learning with Python (Part 2)

  This is a followup to the first article in this series. Once you are comfortable with the concepts explained in that article, you can come back and continue with this.

  https://www.kdnuggets.com/2020/02/audio-data-analysis-deep-learning-python-part-2.html

• Audio Data Analysis Using Deep Learning with Python (Part 1)">Audio Data Analysis Using Deep Learning with Python (Part 1)

  A brief introduction to audio data processing and genre classification using Neural Networks and python.

  https://www.kdnuggets.com/2020/02/audio-data-analysis-deep-learning-python-part-1.html

• 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)

  2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.

  https://www.kdnuggets.com/2020/02/ai-data-science-machine-learning-key-terms-2020.html

• Fourier Transformation for a Data Scientist">Fourier Transformation for a Data Scientist

  The article contains a brief intro into Fourier transformation mathematically and its applications in AI.

  https://www.kdnuggets.com/2020/02/fourier-transformation-data-scientist.html

• Easy Image Dataset Augmentation with TensorFlow

  What can we do when we don't have a substantial amount of varied training data? This is a quick intro to using data augmentation in TensorFlow to perform in-memory image transformations during model training to help overcome this data impediment.

  https://www.kdnuggets.com/2020/02/easy-image-dataset-augmentation-tensorflow.html

• Top 10 AI, Machine Learning Research Articles to know">Top 10 AI, Machine Learning Research Articles to know

  We’ve seen many predictions for what new advances are expected in the field of AI and machine learning. Here, we review a “data set” based on what researchers were apparently studying at the turn of the decade to take a fresh glimpse into what might come to pass in 2020.

  https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-know.html

• NLP Year in Review — 2019

  In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.

  https://www.kdnuggets.com/2020/01/nlp-year-review-2019.html

• The Book to Start You on Machine Learning">The Book to Start You on Machine Learning

  This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.

  https://www.kdnuggets.com/2020/01/book-start-machine-learning.html

• 5 Ways AI Is Changing The Healthcare Industry

  The healthcare AI market is expected to reach 28 billion dollars by the year 2025. With such exponential growth, AI is undoubtedly likely to bring some drastic changes in the healthcare industry. Let’s look at five ways of how AI has changed the healthcare industry.

  https://www.kdnuggets.com/2020/01/5-ways-ai-changing-healthcare-industry.html

• 10 Free Top Notch Machine Learning Courses">10 Free Top Notch Machine Learning Courses

  Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

  https://www.kdnuggets.com/2019/12/10-free-top-notch-courses-machine-learning.html

• Enabling the Deep Learning Revolution

  Deep learning models are revolutionizing the business and technology world with jaw-dropping performances in one application area after another. Read this post on some of the numerous composite technologies which allow deep learning its complex nonlinearity.

  https://www.kdnuggets.com/2019/12/enabling-deep-learning-revolution.html

• Data Science Curriculum Roadmap">Data Science Curriculum Roadmap

  What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

  https://www.kdnuggets.com/2019/12/data-science-curriculum-roadmap.html

• Pro Tips: How to deal with Class Imbalance and Missing Labels

  Your spectacularly-performing machine learning model could be subject to the common culprits of class imbalance and missing labels. Learn how to handle these challenges with techniques that remain open areas of new research for addressing real-world machine learning problems.

  https://www.kdnuggets.com/2019/11/tips-class-imbalance-missing-labels.html

• Deep Learning for Image Classification with Less Data

  In this blog I will be demonstrating how deep learning can be applied even if we don’t have enough data.

  https://www.kdnuggets.com/2019/11/deep-learning-image-classification-less-data.html

• Research Guide for Depth Estimation with Deep Learning

  In this guide, we’ll look at papers aimed at solving the problems of depth estimation using deep learning.

  https://www.kdnuggets.com/2019/11/research-guide-depth-estimation-deep-learning.html

• How to Become a Successful Healthcare Data Analyst

  Are you interested in starting your career in the data analysis domain? Read this informative blog on how to get your career off the ground.

  https://www.kdnuggets.com/2019/11/become-successful-healthcare-data-analyst.html

• How to Build Your Own Logistic Regression Model in Python

  A hands on guide to Logistic Regression for aspiring data scientist and machine learning engineer.

  https://www.kdnuggets.com/2019/10/build-logistic-regression-model-python.html

• Research Guide for Transformers

  The problem with RNNs and CNNs is that they aren’t able to keep up with context and content when sentences are too long. This limitation has been solved by paying attention to the word that is currently being operated on. This guide will focus on how this problem can be addressed by Transformers with the help of deep learning.

  https://www.kdnuggets.com/2019/10/research-guide-transformers.html

• Research Guide for Video Frame Interpolation with Deep Learning

  In this research guide, we’ll look at deep learning papers aimed at synthesizing video frames within an existing video.

  https://www.kdnuggets.com/2019/10/research-guide-video-frame-interpolation-deep-learning.html

• Beyond Word Embedding: Key Ideas in Document Embedding

  This literature review on document embedding techniques thoroughly covers the many ways practitioners develop rich vector representations of text -- from single sentences to entire books.

  https://www.kdnuggets.com/2019/10/beyond-word-embedding-document-embedding.html

• How AI will transform healthcare (and can it fix the US healthcare system?)">How AI will transform healthcare (and can it fix the US healthcare system?)

  This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.

  https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html

• What is Hierarchical Clustering?

  The article contains a brief introduction to various concepts related to Hierarchical clustering algorithm.

  https://www.kdnuggets.com/2019/09/hierarchical-clustering.html

• A 2019 Guide for Automatic Speech Recognition

  In this article, we’ll look at a couple of papers aimed at solving the problem of automated speech recognition with machine and deep learning.

  https://www.kdnuggets.com/2019/09/2019-guide-automatic-speech-recognition.html

• 12 Deep Learning Researchers and Leaders">12 Deep Learning Researchers and Leaders

  Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.

  https://www.kdnuggets.com/2019/09/12-deep-learning-research-leaders.html

• A Single Function to Streamline Image Classification with Keras

  We show, step-by-step, how to construct a single, generalized, utility function to pull images automatically from a directory and train a convolutional neural net model.

  https://www.kdnuggets.com/2019/09/single-function-streamline-image-classification-keras.html

• Explore the world of Bioinformatics with Machine Learning">Explore the world of Bioinformatics with Machine Learning

  The article contains a brief introduction of Bioinformatics and how a machine learning classification algorithm can be used to classify the type of cancer in each patient by their gene expressions.

  https://www.kdnuggets.com/2019/09/explore-world-bioinformatics-machine-learning.html

• A Friendly Introduction to Support Vector Machines

  This article explains the Support Vector Machines (SVM) algorithm in an easy way.

  https://www.kdnuggets.com/2019/09/friendly-introduction-support-vector-machines.html

• Beyond Neurons: Five Cognitive Functions of the Human Brain that we are Trying to Recreate with Artificial Intelligence

  The quest for recreating cognitive capabilities of the brain in deep neural networks remains one of the elusive goals of AI. Let’s explore some human cognitive skills that are serving as inspiration to a new generation of AI techniques.

  https://www.kdnuggets.com/2019/09/beyond-neurons-five-cognitive-functions-human-brain-recreate-artificial-intelligence.html

• A 2019 Guide to Human Pose Estimation

  Human pose estimation refers to the process of inferring poses in an image. Essentially, it entails predicting the positions of a person’s joints in an image or video. This problem is also sometimes referred to as the localization of human joints.

  https://www.kdnuggets.com/2019/08/2019-guide-human-pose-estimation.html

• Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference?

  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.

  https://www.kdnuggets.com/2019/08/artificial-intelligence-vs-machine-learning-vs-deep-learning-difference.html

• A 2019 Guide to Semantic Segmentation

  Semantic segmentation refers to the process of linking each pixel in an image to a class label. These labels could include a person, car, flower, piece of furniture, etc., just to mention a few. We’ll now look at a number of research papers on covering state-of-the-art approaches to building semantic segmentation models.

  https://www.kdnuggets.com/2019/08/2019-guide-semantic-segmentation.html

• Keras Callbacks Explained In Three Minutes

  A gentle introduction to callbacks in Keras. Learn about EarlyStopping, ModelCheckpoint, and other callback functions with code examples.

  https://www.kdnuggets.com/2019/08/keras-callbacks-explained-three-minutes.html

• Introduction to Image Segmentation with K-Means clustering

  Image segmentation is the classification of an image into different groups. Many kinds of research have been done in the area of image segmentation using clustering. In this article, we will explore using the K-Means clustering algorithm to read an image and cluster different regions of the image.

  https://www.kdnuggets.com/2019/08/introduction-image-segmentation-k-means-clustering.html

• Knowing Your Neighbours: Machine Learning on Graphs">Knowing Your Neighbours: Machine Learning on Graphs

  Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.

  https://www.kdnuggets.com/2019/08/neighbours-machine-learning-graphs.html

• Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree

  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.

  https://www.kdnuggets.com/2019/08/pytorch-cheat-sheet-beginners.html

• A 2019 Guide to Object Detection

  Object detection has been applied widely in video surveillance, self-driving cars, and object/people tracking. In this piece, we’ll look at the basics of object detection and review some of the most commonly-used algorithms and a few brand new approaches, as well.

  https://www.kdnuggets.com/2019/08/2019-guide-object-detection.html

• From Data Pre-processing to Optimizing a Regression Model Performance

  All you need to know about data pre-processing, and how to build and optimize a regression model using Backward Elimination method in Python.

  https://www.kdnuggets.com/2019/07/data-pre-processing-optimizing-regression-model-performance.html

• Adapters: A Compact and Extensible Transfer Learning Method for NLP

  Adapters obtain comparable results to BERT on several NLP tasks while achieving parameter efficiency.

  https://www.kdnuggets.com/2019/07/adapters-compact-extensible-transfer-learning-method-nlp.html

• Classifying Heart Disease Using K-Nearest Neighbors

  I have written this post for the developers and assumes no background in statistics or mathematics. The focus is mainly on how the k-NN algorithm works and how to use it for predictive modeling problems.

  https://www.kdnuggets.com/2019/07/classifying-heart-disease-using-k-nearest-neighbors.html

• 10 New Things I Learnt from fast.ai Course V3

  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.

  https://www.kdnuggets.com/2019/06/things-learnt-fastai-course.html

• Building a Computer Vision Model: Approaches and datasets

  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.

  https://www.kdnuggets.com/2019/05/computer-vision-model-approaches-datasets.html

• Top Data Science and Machine Learning Methods Used in 2018, 2019">Top Data Science and Machine Learning Methods Used in 2018, 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.

  https://www.kdnuggets.com/2019/04/top-data-science-machine-learning-methods-2018-2019.html

• An introduction to explainable AI, and why we need it

  We introduce explainable AI, why it is needed, and present the Reversed Time Attention Model, Local Interpretable Model-Agnostic Explanation and Layer-wise Relevance Propagation.

  https://www.kdnuggets.com/2019/04/introduction-explainable-ai.html

• Spatio-Temporal Statistics: A Primer

  Marketing scientist Kevin Gray asks University of Missouri Professor Chris Wikle about Spatio-Temporal Statistics and how it can be used in science and business.

  https://www.kdnuggets.com/2019/04/spatio-temporal-statistics-primer.html

• Another 10 Free Must-See Courses for Machine Learning and Data Science">Another 10 Free Must-See Courses for Machine Learning and Data Science

  Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.

  https://www.kdnuggets.com/2019/04/another-10-free-must-see-courses-machine-learning-data-science.html

• Deep Compression: Optimization Techniques for Inference & Efficiency

  We explain deep compression for improved inference efficiency, mobile applications, and regularization as technology cozies up to the physical limits of Moore's law.

  https://www.kdnuggets.com/2019/03/deep-compression-optimization-techniques-inference-efficiency.html

• How to do Everything in Computer Vision

  The many standard tasks in computer vision all require special consideration: classification, detection, segmentation, pose estimation, enhancement and restoration, and action recognition. Let me show you how to do everything in Computer Vision with Deep Learning!

  https://www.kdnuggets.com/2019/02/everything-computer-vision.html

• State of the art in AI and Machine Learning – highlights of papers with code

  We introduce papers with code, the free and open resource of state-of-the-art Machine Learning papers, code and evaluation tables.

  https://www.kdnuggets.com/2019/02/paperswithcode-ai-machine-learning-highlights.html

• A Quick Guide to Feature Engineering

  Feature engineering plays a key role in machine learning, data mining, and data analytics. This article provides a general definition for feature engineering, together with an overview of the major issues, approaches, and challenges of the field.

  https://www.kdnuggets.com/2019/02/quick-guide-feature-engineering.html

• Trending Deep Learning Github Repositories

  Check these pair of resources for trending and top GitHub deep learning repositories for some new ideas on what to be looking out for.

  https://www.kdnuggets.com/2019/02/trending-top-deep-learning-github-repositories.html