Search results for learn R
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Model Evaluation Metrics in Machine Learning">Model Evaluation Metrics in Machine Learning
A detailed explanation of model evaluation metrics to evaluate a classification machine learning model.https://www.kdnuggets.com/2020/05/model-evaluation-metrics-machine-learning.html
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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
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Faster machine learning on larger graphs with NumPy and Pandas
One of the most exciting features of StellarGraph 1.0 is a new graph data structure — built using NumPy and Pandas — that results in significantly lower memory usage and faster construction times.https://www.kdnuggets.com/2020/05/faster-machine-learning-larger-graphs-numpy-pandas.html
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Interactive Machine Learning Experiments
Dive into experimenting with machine learning techniques using this open-source collection of interactive demos built on multilayer perceptrons, convolutional neural networks, and recurrent neural networks. Each package consists of ready-to-try web browser interfaces and fully-developed notebooks for you to fine tune the training for better performance.https://www.kdnuggets.com/2020/05/interactive-machine-learning-experiments.html
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10 Useful Machine Learning Practices For Python Developers
While you may be a data scientist, you are still a developer at the core. This means your code should be skillful. Follow these 10 tips to make sure you quickly deliver bug-free machine learning solutions.https://www.kdnuggets.com/2020/05/10-useful-machine-learning-practices-python-developers.html
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Top Stories, May 18-24: The Best NLP with Deep Learning Course is Free
Also: Automated Machine Learning: The Free eBook; Sparse Matrix Representation in Python; Build and deploy your first machine learning web app; Complex logic at breakneck speed: Try Julia for data sciencehttps://www.kdnuggets.com/2020/05/top-news-week-0518-0524.html
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The Best NLP with Deep Learning Course is Free">The Best NLP with Deep Learning Course is Free
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
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Build and deploy your first machine learning web app">Build and deploy your first machine learning web app
A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret.https://www.kdnuggets.com/2020/05/build-deploy-machine-learning-web-app.html
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Top KDnuggets tweets, May 13-19: Linear algebra and optimization and machine learning: A textbook
Also: Everything you need to become a self-taught #MachineLearning Engineer ; SQL Cheat Sheet (2020) - a useful cheat sheet that documents some of the more commonly used elements of SQL;https://www.kdnuggets.com/2020/05/top-tweets-may13-19.html
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What they do not tell you about machine learning
There's a lot of excitement out there about machine learning jobs. So, it's always good to start off with a healthy dose of reality and proper expectations.https://www.kdnuggets.com/2020/05/not-tell-machine-learning.html
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Linear algebra and optimization and machine learning: A textbook
This book teaches linear algebra and optimization as the primary topics of interest, and solutions to machine learning problems as applications of these methods. Therefore, the book also provides significant exposure to machine learning.https://www.kdnuggets.com/2020/05/charu-linear-algebra-optimization-machine-learning-textbook.html
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Automated Machine Learning: The Free eBook">Automated Machine Learning: The Free eBook
There is a lot to learn about automated machine learning theory and practice. This free eBook can get you started the right way.https://www.kdnuggets.com/2020/05/automated-machine-learning-free-ebook.html
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AI and Machine Learning for Healthcare">AI and Machine Learning for Healthcare
Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques.https://www.kdnuggets.com/2020/05/ai-machine-learning-healthcare.html
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DeepMind’s Suggestions for Learning #AtHomeWithAI
DeepMind has been sharing resources for learning AI at home on their Twitter account. Check out a few of these suggestions here, and keep your eye on the #AtHomeWithAI hashtag for more.https://www.kdnuggets.com/2020/05/deepmind-suggested-resources-learning-ai.html
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I Designed My Own Machine Learning and AI Degree
With so many pioneering online resources for open education, check out this organized collection of courses you can follow to become a well-rounded machine learning and AI engineer.https://www.kdnuggets.com/2020/05/designed-machine-learning-ai-degree.html
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Machine Learning in Power BI using PyCaret
Check out this step-by-step tutorial for implementing machine learning in Power BI within minutes.https://www.kdnuggets.com/2020/05/machine-learning-power-bi-pycaret.html
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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
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The Elements of Statistical Learning: The Free eBook
Check out this free ebook covering the elements of statistical learning, appropriately titled "The Elements of Statistical Learning."https://www.kdnuggets.com/2020/05/elements-statistical-learning-free-ebook.html
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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
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The Architecture Used at LinkedIn to Improve Feature Management in Machine Learning Models
The new typed feature schema streamlined the reusability of features across thousands of machine learning models.https://www.kdnuggets.com/2020/05/architecture-linkedin-feature-management-machine-learning-models.html
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Will Machine Learning Engineers Exist in 10 Years?
As can be common in many technical fields, the landscape of specialized roles is evolving quickly. With more people learning at least a little machine learning, this could eventually become a common skill set for every software engineer.https://www.kdnuggets.com/2020/05/machine-learning-engineers-not-exist-10-years.html
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Hyperparameter Optimization for Machine Learning Models
Check out this comprehensive guide to model optimization techniques.https://www.kdnuggets.com/2020/05/hyperparameter-optimization-machine-learning-models.html
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Explaining “Blackbox” Machine Learning Models: Practical Application of SHAP
Train a "blackbox" GBM model on a real dataset and make it explainable with SHAP.https://www.kdnuggets.com/2020/05/explaining-blackbox-machine-learning-models-practical-application-shap.html
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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
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Deep Learning: The Free eBook">Deep Learning: The Free eBook
"Deep Learning" is the quintessential book for understanding deep learning theory, and you can still read it freely online.https://www.kdnuggets.com/2020/05/deep-learning-free-ebook.html
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Optimize Response Time of your Machine Learning API In Production
This article demonstrates how building a smarter API serving Deep Learning models minimizes the response time.https://www.kdnuggets.com/2020/05/optimize-response-time-machine-learning-api-production.html
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10 Best Machine Learning Textbooks that All Data Scientists Should Read
Check out these 10 books that can help data scientists and aspiring data scientists learn machine learning today.https://www.kdnuggets.com/2020/04/10-best-machine-learning-textbooks-data-scientists.html
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Fighting Coronavirus With AI: Improving Testing with Deep Learning and Computer Vision
This post will cover how testing is done for the coronavirus, why it's important in battling the pandemic, and how deep learning tools for medical imaging can help us improve the quality of COVID-19 testing.https://www.kdnuggets.com/2020/04/fighting-coronavirus-ai-improving-testing-deep-learning-computer-vision.html
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Math and Architectures of Deep Learning
This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. You can save 40% off Math and Architectures of Deep Learning until May 13! Just enter the code nlkdarch40 at checkout when you buy from manning.com.https://www.kdnuggets.com/2020/04/manning-math-architectures-deep-learning.html
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Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition">Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition
If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.https://www.kdnuggets.com/2020/04/machine-learning-data-science-books-courses-quarantine.html
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A Key Missing Part of the Machine Learning Stack
With many organizations having machine learning models running in production, some are discovering that inefficiencies exists in the first step of the process: feature definition and extraction. Robust feature management is now being realized as a key missing part of the ML stack, and improving it by applying standard software development practices is gaining attention.https://www.kdnuggets.com/2020/04/missing-part-machine-learning-stack.html
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4 Steps to ensure your AI/Machine Learning system survives COVID-19
Many AI models rely on historical data to make predictions on future behavior. So, what happens when consumer behavior across the planet makes a 180 degree flip? Companies are quickly seeing less value from some AI systems as training data is no longer relevant when user behaviors and preferences change so drastically. Those who are flexible can make it through this crisis in data, and these four techniques will help you stay in front of the competition.https://www.kdnuggets.com/2020/04/ai-machine-learning-system-survives-covid-19.html
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State of the Machine Learning and AI Industry
Enterprises are struggling to launch machine learning models that encapsulate the optimization of business processes. These are now the essential components of data-driven applications and AI services that can improve legacy rule-based business processes, increase productivity, and deliver results. In the current state of the industry, many companies are turning to off-the-shelf platforms to increase expectations for success in applying machine learning.https://www.kdnuggets.com/2020/04/machine-learning-ai-industry.html
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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
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Better notebooks through CI: automatically testing documentation for graph machine learning
In this article, we’ll walk through the detailed and helpful continuous integration (CI) that supports us in keeping StellarGraph’s demos current and informative.https://www.kdnuggets.com/2020/04/better-notebooks-through-ci-automatically-testing-documentation-graph-machine-learning.html
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Federated Learning: An Introduction
Improving machine learning models and making them more secure by training on decentralized data.https://www.kdnuggets.com/2020/04/federated-learning-introduction.html
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Visualizing Decision Trees with Python (Scikit-learn, Graphviz, Matplotlib)
Learn about how to visualize decision trees using matplotlib and Graphviz.https://www.kdnuggets.com/2020/04/visualizing-decision-trees-python.html
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Can Java Be Used for Machine Learning and Data Science?">Can Java Be Used for Machine Learning and Data Science?
While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.https://www.kdnuggets.com/2020/04/java-used-machine-learning-data-science.html
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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
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Upcoming Webinars and online events in AI, Data Science, Machine Learning
Use the time at home productively and learn something new! We bring you a selection of upcoming interesting webinars and online events on AI, Data Science, Machine Learning, and related topics.https://www.kdnuggets.com/2020/04/upcoming-webinars-online-events.html
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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
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3 Reasons to Use Random Forest® Over a Neural Network: Comparing Machine Learning versus Deep Learning
Both the random forest algorithm and Neural Networks are different techniques that learn differently but can be used in similar domains. Why would you use one over the other?https://www.kdnuggets.com/2020/04/3-reasons-random-forest-neural-network-comparison.html
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2 Things You Need to Know about Reinforcement Learning – Computational Efficiency and Sample Efficiency
Experimenting with different strategies for a reinforcement learning model is crucial to discovering the best approach for your application. However, where you land can have significant impact on your system's energy consumption that could cause you to think again about the efficiency of your computations.https://www.kdnuggets.com/2020/04/2-things-reinforcement-learning.html
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Microsoft Research Uses Transfer Learning to Train Real-World Autonomous Drones
The new research uses policies learned in simulations in real world drone environments.https://www.kdnuggets.com/2020/03/microsoft-research-transfer-learning-train-real-world-autonomous-drones.html
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How (not) to use Machine Learning for time series forecasting: The sequel">How (not) to use Machine Learning for time series forecasting: The sequel
Developing machine learning predictive models from time series data is an important skill in Data Science. While the time element in the data provides valuable information for your model, it can also lead you down a path that could fool you into something that isn't real. Follow this example to learn how to spot trouble in time series data before it's too late.https://www.kdnuggets.com/2020/03/machine-learning-time-series-forecasting-sequel.html
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Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?
Deep Learning sits at the forefront of many important advances underway in machine learning. With backpropagation being a primary training method, its computational inefficiencies require sophisticated hardware, such as GPUs. Learn about this recent breakthrough algorithmic advancement with improvements to the backpropgation calculations on a CPU that outperforms large neural network training with a GPU.https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html
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Making sense of ensemble learning techniques
This article breaks down ensemble learning and how it can be used for problem solving.https://www.kdnuggets.com/2020/03/making-sense-ensemble-learning-techniques.html
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Diffusion Map for Manifold Learning, Theory and Implementation
This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.https://www.kdnuggets.com/2020/03/diffusion-map-manifold-learning-theory-implementation.html
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Top AI Resources – Directory for Remote Learning
Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.https://www.kdnuggets.com/2020/03/top-ai-resources-remote-learning.html
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Made With ML: Discover, build, and showcase machine learning projects
This is a short introduction to Made With ML, a useful resource for machine learning engineers looking to get ideas for projects to build, and for those looking to share innovative portfolio projects once built.https://www.kdnuggets.com/2020/03/made-with-ml.html
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Exploring TensorFlow Quantum, Google’s New Framework for Creating Quantum Machine Learning Models
TensorFlow Quantum allow data scientists to build machine learning models that work on quantum architectures.https://www.kdnuggets.com/2020/03/tensorflow-quantum-framework-quantum-machine-learning-models.html
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Topic: Machine Learning
This page features most recent and most popular posts on Machine Learning.https://www.kdnuggets.com/topic/machine-learning
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Nine lessons learned during my first year as a Data Scientist">Nine lessons learned during my first year as a Data Scientist
What is it like to be a Data Scientist? There can be many hats to wear, and so many problems to solve that are fed with data, churned by data science, and guided by business results. Find out about lessons learned from one Data Scientist about how best to work and perform in the role.https://www.kdnuggets.com/2020/03/nine-lessons-first-year-data-scientist.html
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The 4 Best Jupyter Notebook Environments for Deep Learning
Many cloud providers, and other third-party services, see the value of a Jupyter notebook environment which is why many companies now offer cloud hosted notebooks that are hosted on the cloud. Let's have a look at 3 such environments.https://www.kdnuggets.com/2020/03/4-best-jupyter-notebook-environments-deep-learning.html
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A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM)">A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM)
Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.https://www.kdnuggets.com/2020/03/machine-learning-algorithm-svm-explained.html
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Building a Mature Machine Learning Team
After spending a lot of time thinking about the paths that software companies take toward ML maturity, this framework was created to follow as you adopt ML and then mature as an organization. The framework covers every aspect of building a team including product, process, technical, and organizational readiness, as well as recognizes the importance of cross-functional expertise and process improvements for bringing AI-driven products to market.https://www.kdnuggets.com/2020/03/mature-machine-learning-team.html
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The Most Useful Machine Learning Tools of 2020
This articles outlines 5 sets of tools every lazy full-stack data scientist should use.https://www.kdnuggets.com/2020/03/most-useful-machine-learning-tools-2020.html
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Decision Boundary for a Series of Machine Learning Models
I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different Machine Learning models make predictions.https://www.kdnuggets.com/2020/03/decision-boundary-series-machine-learning-models.html
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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
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Top KDnuggets tweets, Mar 04-10: 10 Free Must-Read Books for Machine Learning and Data Science
Also: The three phases of #COVID19 – and how we can make it manageable; 50 Must-Read Free Books For Every Data Scientist in 2020; Binary classification is a core machine learning technique, but is there a better way to evaluate its performance than ROC-AUC?https://www.kdnuggets.com/2020/03/top-tweets-mar04-10.html
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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
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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
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A Crash Course in Game Theory for Machine Learning: Classic and New Ideas
Game theory is experiencing a renaissance driven by the evolution of AI. What are some classic and new ideas that data scientists should be aware of.https://www.kdnuggets.com/2020/03/crash-course-game-theory-machine-learning.html
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Resources for Women in AI, Data Science, and Machine Learning">Resources for Women in AI, Data Science, and Machine Learning
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.https://www.kdnuggets.com/2020/03/resources-women-ai-data-science-machine-learning.html
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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
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Trends in Machine Learning in 2020
Many industries realize the potential of Machine Learning and are incorporating it as a core technology. Progress and new applications of these tools are moving quickly in the field, and we discuss expected upcoming trends in Machine Learning for 2020.https://www.kdnuggets.com/2020/03/trends-machine-learning-2020.html
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The Augmented Scientist Part 1: Practical Application Machine Learning in Classification of SEM Images
Our goal here is to see if we can build a classifier that can identify patterns in Scanning Electron Microscope (SEM) images, and compare the performance of our classifier to the current state-of-the-art.https://www.kdnuggets.com/2020/03/the-augmented-scientist-practical-application-machine-learning-classification-images.html
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Topic: Deep Learning
This page features most recent and most popular posts on Deep Learning.https://www.kdnuggets.com/topic/deep-learning
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20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)
We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.https://www.kdnuggets.com/2020/03/ai-data-science-machine-learning-key-terms-part2.html
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Uber Unveils a New Service for Backtesting Machine Learning Models at Scale
The transportation giant built a new service and architecture for backtesting forecasting models.https://www.kdnuggets.com/2020/03/uber-unveils-service-backtesting-machine-learning-models-scale.html
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Free Mathematics Courses for Data Science & Machine Learning">Free Mathematics Courses for Data Science & Machine Learning
It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.https://www.kdnuggets.com/2020/02/free-mathematics-courses-data-science-machine-learning.html
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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
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Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms">Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms
The Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms has the largest number of leaders ever. We examine the leaders and changes and trends vs previous years.https://www.kdnuggets.com/2020/02/gartner-mq-2020-data-science-machine-learning.html
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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
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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
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Inside The Machine Learning that Google Used to Build Meena: A Chatbot that Can Chat About Anything
Meena is one of the major milestones in the history of NLU. How did Google build it?https://www.kdnuggets.com/2020/02/inside-machine-learning-google-build-meena-chatbot.html
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What Does it Mean to Deploy a Machine Learning Model?
You are a Data Scientist who knows how to develop machine learning models. You might also be a Data Scientist who is too afraid to ask how to deploy your machine learning models. The answer isn't entirely straightforward, and so is a major pain point of the community. This article will help you take a step in the right direction for production deployments that are automated, reproducible, and auditable.https://www.kdnuggets.com/2020/02/deploy-machine-learning-model.html
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Sharing your machine learning models through a common API
DEEPaaS API is a software component developed to expose machine learning models through a REST API. In this article we describe how to do it.https://www.kdnuggets.com/2020/02/sharing-machine-learning-models-common-api.html
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How to learn data science on your own: a practical guide
While much focus today is on the rise in working from home and the challenges experienced, not as much is said about learning from home. For those lone wolfs studying Data Science in a self-directed way, a range of issues can get in the way of your goal. Learn about these common problems to prepare to focus yourself all the way to your educational goals.https://www.kdnuggets.com/2020/02/learn-data-science-guide.html
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Amazon Uses Self-Learning to Teach Alexa to Correct its Own Mistakes
The digital assistant incorporates a reformulation engine that can learn to correct responses in real time based on customer interactions.https://www.kdnuggets.com/2020/02/amazon-uses-self-learning-teach-alexa-correct-mistakes.html
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AI and Machine Learning In Our Every Day Life
The curiosity and buzz around the most talked-about technology -- Artificial Intelligence -- have experts and technophiles busy decoding its exciting future applications. Of course, the use of AI and machine learning is already pervasive in our daily lives, as we review many of these popular features in this article.https://www.kdnuggets.com/2020/02/ai-machine-learning-everyday-life.html
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Intro to Machine Learning and AI based on high school knowledge
Machine learning information is becoming pervasive in the media as well as a core skill in new, important job sectors. Getting started in the field can require learning complex concepts, and this article outlines an approach on how to begin learning about these exciting topics based on high school knowledge.https://www.kdnuggets.com/2020/02/intro-machine-learning-ai.html
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Serverless Machine Learning with R on Cloud Run
Expedite the deployment of your machine models using serverless cloud infrastructure. In this tutorial, we explore creating and deploying a model which scraps real time Twitter data and returns interactive visualization using R.https://www.kdnuggets.com/2020/02/serverless-machine-learning-r-cloud-run.html
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Why are Machine Learning Projects so Hard to Manage?
What makes deploying a machine learning project so difficult? Is it the expectations? The people? The tech? There are common threads to these challenges, and best practices exist to deal with them.https://www.kdnuggets.com/2020/02/machine-learning-projects-manage.html
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Past 2020 Meetings / Online Events on AI, Analytics, Big Data, Data Science, and Machine Learning
Past | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec Read more »https://www.kdnuggets.com/meetings/past-meetings-2020.html
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Data Validation for Machine Learning">Data Validation for Machine Learning
While the validation process cannot directly find what is wrong, the process can show us sometimes that there is a problem with the stability of the model.https://www.kdnuggets.com/2020/01/data-validation-machine-learning.html
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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
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Managing Machine Learning Cycles: Five Learnings from comparing Data Science Experimentation/ Collaboration Tools
Machine learning projects require handling different versions of data, source code, hyperparameters, and environment configuration. Numerous tools are on the market for managing this variety, and this review features important lessons learned from an ongoing evaluation of the current landscape.https://www.kdnuggets.com/2020/01/managing-machine-learning-cycles.html
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Exoplanet Hunting Using Machine Learning
Search for exoplanets — those planets beyond our own solar system — using machine learning, and implement these searches in Python.https://www.kdnuggets.com/2020/01/exoplanet-hunting-machine-learning.html
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Uber Has Been Quietly Assembling One of the Most Impressive Open Source Deep Learning Stacks in the Market
Many of the technologies used by Uber teams have been open sourced and received accolades from the machine learning community. Let’s look at some of my favorites.https://www.kdnuggets.com/2020/01/uber-quietly-assembling-impressive-open-source-deep-learning.html
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Semi-supervised learning with Generative Adversarial Networks
The paper discussed in this post, Semi-supervised learning with Generative Adversarial Networks, utilizes a GAN architecture for multi-label classification.https://www.kdnuggets.com/2020/01/semi-supervised-learning-generative-adversarial-networks.html
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Random Forest® — A Powerful Ensemble Learning Algorithm
The article explains the Random Forest algorithm and how to build and optimize a Random Forest classifier.https://www.kdnuggets.com/2020/01/random-forest-powerful-ensemble-learning-algorithm.html
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Explaining Black Box Models: Ensemble and Deep Learning Using LIME and SHAP
This article will demonstrate explainability on the decisions made by LightGBM and Keras models in classifying a transaction for fraudulence, using two state of the art open source explainability techniques, LIME and SHAP.https://www.kdnuggets.com/2020/01/explaining-black-box-models-ensemble-deep-learning-lime-shap.html
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The Future of Machine Learning
This summary overviews the keynote at TensorFlow World by Jeff Dean, Head of AI at Google, that considered the advancements of computer vision and language models and predicted the direction machine learning model building should follow for the future.https://www.kdnuggets.com/2020/01/future-machine-learning.html
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Top 9 Mobile Apps for Learning and Practicing Data Science">Top 9 Mobile Apps for Learning and Practicing Data Science
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.https://www.kdnuggets.com/2020/01/top-9-mobile-apps-learning-practicing-data-science.html
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Classify A Rare Event Using 5 Machine Learning Algorithms
Which algorithm works best for unbalanced data? Are there any tradeoffs?https://www.kdnuggets.com/2020/01/classify-rare-event-machine-learning-algorithms.html
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Graph Machine Learning Meets UX: An uncharted love affair
When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.https://www.kdnuggets.com/2020/01/graph-machine-learning-ux.html
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Applying Occam’s razor to Deep Learning
Finding a deep learning model to perform well is an exciting feat. But, might there be other -- less complex -- models that perform just as well for your application? A simple complexity measure based on the statistical physics concept of Cascading Periodic Spectral Ergodicity (cPSE) can help us be computationally efficient by considering the least complex during model selection.https://www.kdnuggets.com/2020/01/occams-razor-deep-learning.html
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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
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Learning SQL the Hard Way">Learning SQL the Hard Way
Simply put: This post is about installing SQL, explaining SQL and running SQL.https://www.kdnuggets.com/2020/01/learning-sql-hard-way.html
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10 Python Tips and Tricks You Should Learn Today">10 Python Tips and Tricks You Should Learn Today
Check out this collection of 10 Python snippets that can be taken as a reference for your daily work.https://www.kdnuggets.com/2020/01/10-python-tips-tricks-learn-today.html
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Introducing Generalized Integrated Gradients (GIG): A Practical Method for Explaining Diverse Ensemble Machine Learning Models
There is a need for a new way to explain complex, ensembled ML models for high-stakes applications such as credit and lending. This is why we invented GIG.https://www.kdnuggets.com/2020/01/generalized-integrated-gradients-explaining-ensemble-models.html
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H2O Framework for Machine Learning
This article is an overview of H2O, a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks.https://www.kdnuggets.com/2020/01/h2o-framework-machine-learning.html
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Accuracy vs Speed – what Data Scientists can learn from Search
Delivering accurate insights is the core function of any data scientist. Navigating the development road toward this goal can sometimes be tricky, especially when cross-collaboration is required, and these lessons learned from building a search application will help you negotiate the demands between accuracy and speed.https://www.kdnuggets.com/2020/01/accuracy-speed-search.html
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Automated Machine Learning: How do teams work together on an AutoML project?">Automated Machine Learning: How do teams work together on an AutoML project?
In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machine learning and Azure Machine Learning service to reduce product overstock.https://www.kdnuggets.com/2020/01/teams-work-together-automl-project.html
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How To “Ultralearn” Data Science: summary, for those in a hurry">How To “Ultralearn” Data Science: summary, for those in a hurry
For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.https://www.kdnuggets.com/2019/12/ultralearn-data-science-summary.html
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How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4
In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.https://www.kdnuggets.com/2019/12/ultralearn-data-science-deep-understanding-experimentation-part4.html
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Fighting Overfitting in Deep Learning
This post outlines an attack plan for fighting overfitting in neural networks.https://www.kdnuggets.com/2019/12/fighting-overfitting-deep-learning.html
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10 Best and Free Machine Learning Courses, Online
Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.https://www.kdnuggets.com/2019/12/best-free-machine-learning-courses-online.html
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The ravages of concept drift in stream learning applications and how to deal with it
Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. These streams of data evolve generally over time and may be occasionally affected by a change (concept drift). How to handle this change by using detection and adaptation mechanisms is crucial in many real-world systems.https://www.kdnuggets.com/2019/12/ravages-concept-drift-stream-learning-applications.html
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How To “Ultralearn” Data Science: removing distractions and finding focus, Part 2
This second part in a series about how to "ultralearn" data science will guide you through several techniques to remove those distractions -- because your focus needs more focus.https://www.kdnuggets.com/2019/12/ultralearn-data-science-distractions-focus-part2.html
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Microsoft Introduces Icebreaker to Address the Famous Ice-Start Challenge in Machine Learning
The new technique allows the deployment of machine learning models that operate with minimum training data.https://www.kdnuggets.com/2019/12/microsoft-introduces-icebreaker-ice-start-challenge-machine-learning.html
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How To “Ultralearn” Data Science, Part 1
What is "ultralearning" and how can you follow the strategy to become an expert of data science? Start with this first part in a series that will guide you through this self-motivated methodology to help you efficiently master difficult skills.https://www.kdnuggets.com/2019/12/ultralearn-data-science-part1.html
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AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020">AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-technology.html
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Deployment of Machine learning models using Flask
This blog will explain the basics of deploying a machine learning algorithm, focusing on developing a Naïve Bayes model for spam message identification, and using Flask to create an API for that model.https://www.kdnuggets.com/2019/12/excelr-deployment-machine-learning-flask.html
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Scalable graph machine learning: a mountain we can climb?
Graph machine learning is a developing area of research that brings many complexities. One challenge that both fascinates and infuriates those working with graph algorithms is — scalability. We take a close look at scalability for graph machine learning methods covering what it is, what makes it difficult, and an example of a method that tackles it head-on.https://www.kdnuggets.com/2019/12/scalable-graph-machine-learning.html
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AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020">AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-research.html
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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
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Why software engineering processes and tools don’t work for machine learning
While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.https://www.kdnuggets.com/2019/12/comet-software-engineering-machine-learning.html
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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
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Lit BERT: NLP Transfer Learning In 3 Steps
PyTorch Lightning is a lightweight framework which allows anyone using PyTorch to scale deep learning code easily while making it reproducible. In this tutorial we’ll use Huggingface's implementation of BERT to do a finetuning task in Lightning.https://www.kdnuggets.com/2019/11/lit-bert-nlp-transfer-learning-3-steps.html
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A Doomed Marriage of Machine Learning and Agile
Sebastian Thrun, the founder of Udacity, ruined my machine learning project and wedding.https://www.kdnuggets.com/2019/11/doomed-marriage-machine-learning-agile.html
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Machine Learning 101: The What, Why, and How of Weighting
Weighting is a technique for improving models. In this article, learn more about what weighting is, why you should (and shouldn’t) use it, and how to choose optimal weights to minimize business costs.https://www.kdnuggets.com/2019/11/machine-learning-what-why-how-weighting.html
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Probability Learning: Naive Bayes
This post will describe various simplifications of Bayes' Theorem, that make it more practical and applicable to real world problems: these simplifications are known by the name of Naive Bayes. Also, to clarify everything we will see a very illustrative example of how Naive Bayes can be applied for classification.https://www.kdnuggets.com/2019/11/probability-learning-naive-bayes.html
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Automated Machine Learning Project Implementation Complexities">Automated Machine Learning Project Implementation Complexities
To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.https://www.kdnuggets.com/2019/11/automl-implementation-complexities.html
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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
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead">Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
The two main takeaways from this paper: firstly, a sharpening of my understanding of the difference between explainability and interpretability, and why the former may be problematic; and secondly some great pointers to techniques for creating truly interpretable models.https://www.kdnuggets.com/2019/11/stop-explaining-black-box-models.html
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The Reinforcement-Learning Methods that Allow AlphaStar to Outcompete Almost All Human Players at StarCraft II
The new AlphaStar achieved Grandmaster level at StarCraft II overcoming some of the limitations of the previous version. How did it do it?https://www.kdnuggets.com/2019/11/reinforcement-learning-methods-alphastar-outcompete-human-players-starcraft.html
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GitHub Repo Raider and the Automation of Machine Learning
Since X never, ever marks the spot, this article raids the GitHub repos in search of quality automated machine learning resources. Read on for projects and papers to help understand and implement AutoML.https://www.kdnuggets.com/2019/11/github-repo-raider-automated-machine-learning.html
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Testing Your Machine Learning Pipelines
Let’s take a look at traditional testing methodologies and how we can apply these to our data/ML pipelines.https://www.kdnuggets.com/2019/11/testing-machine-learning-pipelines.html