Search results for learn R
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Transfer Learning Made Easy: Coding a Powerful Technique
While the revolution of deep learning now impacts our daily lives, these networks are expensive. Approaches in transfer learning promise to ease this burden by enabling the re-use of trained models -- and this hands-on tutorial will walk you through a transfer learning technique you can run on your laptop.https://www.kdnuggets.com/2019/11/transfer-learning-coding.html
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Beginners Guide to the Three Types of Machine Learning
The following article is an introduction to classification and regression — which are known as supervised learning — and unsupervised learning — which in the context of machine learning applications often refers to clustering — and will include a walkthrough in the popular python library scikit-learn.https://www.kdnuggets.com/2019/11/beginners-guide-three-types-machine-learning.html
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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
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Facebook Adds This New Framework to It’s Reinforcement Learning Arsenal
ReAgent is a new framework that streamlines the implementation of reasoning systems.https://www.kdnuggets.com/2019/11/facebook-adds-this-new-framework-reinforcement-learning-arsenal.html
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Research Guide: Advanced Loss Functions for Machine Learning Models
This guide explores research centered on a variety of advanced loss functions for machine learning models.https://www.kdnuggets.com/2019/11/research-guide-advanced-loss-functions-machine-learning-models.html
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Probability Learning: Maximum Likelihood
The maths behind Bayes will be better understood if we first cover the theory and maths underlying another fundamental method of probabilistic machine learning: Maximum Likelihood. This post will be dedicated to explaining it.https://www.kdnuggets.com/2019/11/probability-learning-maximum-likelihood.html
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Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch">Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch
The new release of PyTorch includes some impressive open source projects for deep learning researchers and developers.https://www.kdnuggets.com/2019/11/facebook-quietly-open-sourcing-amazing-deep-learning-capabilities-pytorch.html
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Top Machine Learning Software Tools for Developers">Top Machine Learning Software Tools for Developers
As a developer who is excited about leveraging machine learning for faster and more effective development, these software tools are worth trying out.https://www.kdnuggets.com/2019/11/top-machine-learning-software-developers.html
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What is Machine Learning on Code?
Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.https://www.kdnuggets.com/2019/11/machine-learning-code-mloncode.html
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Why is Machine Learning Deployment Hard?">Why is Machine Learning Deployment Hard?
Developing an excellent machine learning model is one thing. Deploying it to production is another. Consider these lessons learned and recommendations for approaching this important challenge to help ensure value from your AI work.https://www.kdnuggets.com/2019/10/machine-learning-deployment-hard.html
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How to Extend Scikit-learn and Bring Sanity to Your Machine Learning Workflow
In this post, learn how to extend Scikit-learn code to make your experiments easier to maintain and reproduce.https://www.kdnuggets.com/2019/10/extend-scikit-learn-bring-sanity-machine-learning-workflow.html
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How Bayes’ Theorem is Applied in Machine Learning
Learn how Bayes Theorem is in Machine Learning for classification and regression!https://www.kdnuggets.com/2019/10/bayes-theorem-applied-machine-learning.html
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DeepMind is Using This Old Technique to Evaluate Fairness in Machine Learning Models
Visualizing the datasets is an essential component to identify potential sources of bias and unfairness. DeepMind relied on a method called Causal Bayesian networks (CBNs) to represent and estimate unfairness in a dataset.https://www.kdnuggets.com/2019/10/deepmind-using-old-technique-evaluate-fairness-machine-learning-models.html
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Intro to Adversarial Machine Learning and Generative Adversarial Networks
In this crash course on GANs, we explore where they fit into the pantheon of generative models, how they've changed over time, and what the future has in store for this area of machine learning.https://www.kdnuggets.com/2019/10/adversarial-machine-learning-generative-adversarial-networks.html
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Anomaly Detection, A Key Task for AI and Machine Learning, Explained
One way to process data faster and more efficiently is to detect abnormal events, changes or shifts in datasets. Anomaly detection refers to identification of items or events that do not conform to an expected pattern or to other items in a dataset that are usually undetectable by a human expert.https://www.kdnuggets.com/2019/10/anomaly-detection-explained.html
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How to Easily Deploy Machine Learning Models Using Flask
This post aims to make you get started with putting your trained machine learning models into production using Flask API.https://www.kdnuggets.com/2019/10/easily-deploy-machine-learning-models-using-flask.html
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Probability Learning: Bayes’ Theorem
Learn about one of the fundamental theorems of probability with an easy everyday example.https://www.kdnuggets.com/2019/10/probability-learning-bayes-theorem.html
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Top 7 Things I Learned in my Data Science Masters
Even though I’m still in my studies, here’s a list of the most important things I’ve learned (as of yet).https://www.kdnuggets.com/2019/10/top-7-things-learned-data-science-masters.html
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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
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Three Things to Know About Reinforcement Learning
As an engineer, scientist, or researcher, you may want to take advantage of this new and growing technology, but where do you start? The best place to begin is to understand what the concept is, how to implement it, and whether it’s the right approach for a given problem.https://www.kdnuggets.com/2019/10/mathworks-reinforcement-learning.html
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Choosing a Machine Learning Model
Selecting the perfect machine learning model is part art and part science. Learn how to review multiple models and pick the best in both competitive and real-world applications.https://www.kdnuggets.com/2019/10/choosing-machine-learning-model.html
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8 Paths to Getting a Machine Learning Job Interview
While you may be focused on your performance during your next job interview, landing that interview can be just as hard. Check out these tips for finding and securing an interview for a machine learning job.https://www.kdnuggets.com/2019/10/8-paths-machine-learning-job-interview.html
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Activation maps for deep learning models in a few lines of code">Activation maps for deep learning models in a few lines of code
We illustrate how to show the activation maps of various layers in a deep CNN model with just a couple of lines of code.https://www.kdnuggets.com/2019/10/activation-maps-deep-learning-models-lines-code.html
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OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned
OpenAI trained agents in a simple game of hide-and-seek and learned many other different skills in the process.https://www.kdnuggets.com/2019/10/openai-tried-train-ai-agents-play-hide-seek-instead-shocked-learned.html
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Data Preparation for Machine learning 101: Why it’s important and how to do it
As data scientists who are the brains behind the AI-based innovations, you need to understand the significance of data preparation to achieve the desired level of cognitive capability for your models. Let’s begin.https://www.kdnuggets.com/2019/10/data-preparation-machine-learning-101.html
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Multi-Task Learning – ERNIE 2.0: State-of-the-Art NLP Architecture Intuitively Explained
The tech giant Baidu unveiled its state-of-the-art NLP architecture ERNIE 2.0 earlier this year, which scored significantly higher than XLNet and BERT on all tasks in the GLUE benchmark. This major breakthrough in NLP takes advantage of a new innovation called “Continual Incremental Multi-Task Learning”.https://www.kdnuggets.com/2019/10/multi-task-learning-ernie-sota-nlp-architecture.html
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DeepMind Has Quietly Open Sourced Three New Impressive Reinforcement Learning Frameworks
Three new releases that will help researchers streamline the implementation of reinforcement learning programs.https://www.kdnuggets.com/2019/09/deepmind-three-new-impressive-reinforcement-learning-frameworks.html
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Data Mapping Using Machine Learning
Data mapping is a way to organize various bits of data into a manageable and easy-to-understand system.https://www.kdnuggets.com/2019/09/data-mapping-using-machine-learning.html
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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
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Scikit-Learn & More for Synthetic Dataset Generation for Machine Learning
While mature algorithms and extensive open-source libraries are widely available for machine learning practitioners, sufficient data to apply these techniques remains a core challenge. Discover how to leverage scikit-learn and other tools to generate synthetic data appropriate for optimizing and fine-tuning your models.https://www.kdnuggets.com/2019/09/scikit-learn-synthetic-dataset.html
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5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python
“I want to learn machine learning and artificial intelligence, where do I start?” Here.https://www.kdnuggets.com/2019/09/5-beginner-friendly-steps-learn-machine-learning-data-science-python.html
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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
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5 Step Guide to Scalable Deep Learning Pipelines with d6tflow
How to turn a typical pytorch script into a scalable d6tflow DAG for faster research & development.https://www.kdnuggets.com/2019/09/5-step-guide-scalable-deep-learning-pipelines-d6tflow.html
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Cartoon: Unsupervised Machine Learning?">Cartoon: Unsupervised Machine Learning?
New KDnuggets Cartoon looks at one of the hottest directions in Machine Learning and asks "Can Machine Learning be too unsupervised?"https://www.kdnuggets.com/2019/09/cartoon-unsupervised-machine-learning.html
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Many Heads Are Better Than One: The Case For Ensemble Learning
While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.https://www.kdnuggets.com/2019/09/ensemble-learning.html
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Version Control for Data Science: Tracking Machine Learning Models and Datasets
I am a Git god, why do I need another version control system for Machine Learning Projects?https://www.kdnuggets.com/2019/09/version-control-data-science-tracking-machine-learning-models-datasets.html
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Ensemble Methods for Machine Learning: AdaBoost
It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.https://www.kdnuggets.com/2019/09/ensemble-methods-machine-learning-adaboost.html
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Can graph machine learning identify hate speech in online social networks?
Online hate speech is a complex subject. Follow this demonstration using state-of-the-art graph neural network models to detect hateful users based on their activities on the Twitter social network.https://www.kdnuggets.com/2019/09/graph-machine-learning-hate-speech-social-networks.html
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Train sklearn 100x Faster">Train sklearn 100x Faster
As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.https://www.kdnuggets.com/2019/09/train-sklearn-100x-faster.html
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Scikit-Learn vs mlr for Machine Learning
How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.https://www.kdnuggets.com/2019/09/scikit-learn-mlr-machine-learning.html
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Common Machine Learning Obstacles
In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.https://www.kdnuggets.com/2019/09/mathworks-common-machine-learning-obstacles.html
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A 2019 Guide to Speech Synthesis with Deep Learning
In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.https://www.kdnuggets.com/2019/09/2019-guide-speech-synthesis-deep-learning.html
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Advice on building a machine learning career and reading research papers by Prof. Andrew Ng">Advice on building a machine learning career and reading research papers by Prof. Andrew Ng
This blog summarizes the career advice/reading research papers lecture in the CS230 Deep learning course by Stanford University on YouTube, and includes advice from Andrew Ng on how to read research papers.https://www.kdnuggets.com/2019/09/advice-building-machine-learning-career-research-papers-andrew-ng.html
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An Easy Introduction to Machine Learning Recommender Systems
Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches work along with implementations to follow from example code.https://www.kdnuggets.com/2019/09/machine-learning-recommender-systems.html
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Python Libraries for Interpretable Machine Learning">Python Libraries for Interpretable Machine Learning
In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.https://www.kdnuggets.com/2019/09/python-libraries-interpretable-machine-learning.html
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6 Tips for Building a Training Data Strategy for Machine Learning
Without a well-defined approach for collecting and structuring training data, launching an AI initiative becomes an uphill battle. These six recommendations will help you craft a successful strategy.https://www.kdnuggets.com/2019/09/6-tips-training-data-strategy-machine-learning.html
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Jobs in Data Science, Machine Learning, AI & Analytics
To add a free short entry here for a job related to Data Science, Machine Learning, AI or Analytics, email the following 5 items to Read more »https://www.kdnuggets.com/jobs/index.html
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Deep Learning Next Step: Transformers and Attention Mechanism">Deep Learning Next Step: Transformers and Attention Mechanism
With the pervasive importance of NLP in so many of today's applications of deep learning, find out how advanced translation techniques can be further enhanced by transformers and attention mechanisms.https://www.kdnuggets.com/2019/08/deep-learning-transformers-attention-mechanism.html
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Types of Bias in Machine Learning">Types of Bias in Machine Learning
The sample data used for training has to be as close a representation of the real scenario as possible. There are many factors that can bias a sample from the beginning and those reasons differ from each domain (i.e. business, security, medical, education etc.)https://www.kdnuggets.com/2019/08/types-bias-machine-learning.html
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Introducing AI Explainability 360: A New Toolkit to Help You Understand what Machine Learning Models are Doing
Recently, AI researchers from IBM open sourced AI Explainability 360, a new toolkit of state-of-the-art algorithms that support the interpretability and explainability of machine learning models.https://www.kdnuggets.com/2019/08/introducing-ai-explainability-360-toolkit-understand-machine-learning-models.html
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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
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How LinkedIn, Uber, Lyft, Airbnb and Netflix are Solving Data Management and Discovery for Machine Learning Solutions
As machine learning evolves, the need for tools and platforms that automate the lifecycle management of training and testing datasets is becoming increasingly important. Fast growing technology companies like Uber or LinkedIn have been forced to build their own in-house data lifecycle management solutions to power different groups of machine learning models.https://www.kdnuggets.com/2019/08/linkedin-uber-lyft-airbnb-netflix-solving-data-management-discovery-machine-learning-solutions.html
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Is Kaggle Learn a “Faster Data Science Education?”">Is Kaggle Learn a “Faster Data Science Education?”
Kaggle Learn is "Faster Data Science Education," featuring micro-courses covering an array of data skills for immediate application. Courses may be made with newcomers in mind, but the platform and its content is proving useful as a review for more seasoned practitioners as well.https://www.kdnuggets.com/2019/08/kaggle-learn-faster-data-science-education.html
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Deep Learning for NLP: Creating a Chatbot with Keras!">Deep Learning for NLP: Creating a Chatbot with Keras!
Learn how to use Keras to build a Recurrent Neural Network and create a Chatbot! Who doesn’t like a friendly-robotic personal assistant?https://www.kdnuggets.com/2019/08/deep-learning-nlp-creating-chatbot-keras.html
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Understanding Cancer using Machine Learning">Understanding Cancer using Machine Learning
Use of Machine Learning (ML) in Medicine is becoming more and more important. One application example can be Cancer Detection and Analysis.https://www.kdnuggets.com/2019/08/understanding-cancer-machine-learning.html
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Top KDnuggets tweets, Aug 07-13: Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners To Follow
Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs.https://www.kdnuggets.com/2019/08/top-tweets-aug07-13.html
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Statistical Modelling vs Machine Learning">Statistical Modelling vs Machine Learning
At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.https://www.kdnuggets.com/2019/08/statistical-modelling-vs-machine-learning.html
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Learn how to use PySpark in under 5 minutes (Installation + Tutorial)
Apache Spark is one of the hottest and largest open source project in data processing framework with rich high-level APIs for the programming languages like Scala, Python, Java and R. It realizes the potential of bringing together both Big Data and machine learning.https://www.kdnuggets.com/2019/08/learn-pyspark-installation-tutorial.html
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6 Key Concepts in Andrew Ng’s “Machine Learning Yearning”">6 Key Concepts in Andrew Ng’s “Machine Learning Yearning”
If you are diving into AI and machine learning, Andrew Ng's book is a great place to start. Learn about six important concepts covered to better understand how to use these tools from one of the field's best practitioners and teachers.https://www.kdnuggets.com/2019/08/key-concepts-andrew-ng-machine-learning-yearning.html
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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
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Deep Learning for NLP: ANNs, RNNs and LSTMs explained!">Deep Learning for NLP: ANNs, RNNs and LSTMs explained!
Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!https://www.kdnuggets.com/2019/08/deep-learning-nlp-explained.html
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Machine Learning is Happening Now: A Survey of Organizational Adoption, Implementation, and Investment
This is an excerpt from a survey which sought to evaluate the relevance of machine learning in operations today, assess the current state of machine learning adoption and to identify tools used for machine learning. A link to the full report is inside.https://www.kdnuggets.com/2019/08/machine-learning-happening-now-survey-organizational-adoption-implementation-investment.html
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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
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Easily Deploy Deep Learning Models in Production
Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. This blog explores how to navigate these challenges.https://www.kdnuggets.com/2019/08/nvidia-deploy-deep-learning-models-production.html
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Opening Black Boxes: How to leverage Explainable Machine Learning
A machine learning model that predicts some outcome provides value. One that explains why it made the prediction creates even more value for your stakeholders. Learn how Interpretable and Explainable ML technologies can help while developing your model.https://www.kdnuggets.com/2019/08/open-black-boxes-explainable-machine-learning.html
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How a simple mix of object-oriented programming can sharpen your deep learning prototype
By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.https://www.kdnuggets.com/2019/08/simple-mix-object-oriented-programming-sharpen-deep-learning-prototype.html
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Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning">Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning
Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.https://www.kdnuggets.com/2019/07/best-podcasts-ai-analytics-data-science-machine-learning.html
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Decentralized and Collaborative AI: How Microsoft Research is Using Blockchains to Build More Transparent Machine Learning Models
Recently, AI researchers from Microsoft open sourced the Decentralized & Collaborative AI on Blockchain project that enables the implementation of decentralized machine learning models based on blockchain technologies.https://www.kdnuggets.com/2019/07/decentralized-collaborative-ai-microsoft-research-blockchains-transparent-machine-learning.html
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High-Quality AI And Machine Learning Data Labeling At Scale: A Brief Research Report
Analyst firm Cognilytica estimates that as much as 80% of machine learning project time is spent on aggregating, cleaning, labeling, and augmenting machine learning model data. So, how do innovative machine learning teams prepare data in such a way that they can trust its quality, cost of preparation, and the speed with which it’s delivered?https://www.kdnuggets.com/2019/07/high-quality-ai-machine-learning-data-labeling-research-report.html
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Top Certificates and Certifications in Analytics, Data Science, Machine Learning and AI">Top Certificates and Certifications in Analytics, Data Science, Machine Learning and AI
Here are the top certificates and certifications in Analytics, AI, Data Science, Machine Learning and related areas.https://www.kdnuggets.com/2019/07/top-certificates-analytics-data-science-machine-learning-ai.html
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12 Things I Learned During My First Year as a Machine Learning Engineer
Learn about the day-in-the-life of one machine learning engineer and the important lessons learned for being successful in that role.https://www.kdnuggets.com/2019/07/12-things-learned-machine-learning-engineer.html
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Is Bias in Machine Learning all Bad?
We have been taught over our years of predictive model building that bias will harm our model. Bias control needs to be in the hands of someone who can differentiate between the right kind and wrong kind of bias.https://www.kdnuggets.com/2019/07/bias-machine-learning-bad.html
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Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning">Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning
This blog post is an overview of quantum machine learning written by the author of the paper Bayesian deep learning on a quantum computer. In it, we explore the application of machine learning in the quantum computing space. The authors of this paper hope that the results of the experiment help influence the future development of quantum machine learning.https://www.kdnuggets.com/2019/07/bayesian-deep-learning-near-term-quantum-computers.html
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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
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Things I Have Learned About Data Science
Read this collection of 38 things the author has learned along his travels, and has opted to share for the benefit of the reader.https://www.kdnuggets.com/2019/07/collection-things-learned-data-science.html
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Dealing with categorical features in machine learning">Dealing with categorical features in machine learning
Many machine learning algorithms require that their input is numerical and therefore categorical features must be transformed into numerical features before we can use any of these algorithms.https://www.kdnuggets.com/2019/07/categorical-features-machine-learning.html
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Scaling a Massive State-of-the-art Deep Learning Model in Production
A new NLP text writing app based on OpenAI's GPT-2 aims to write with you -- whenever you ask. Find out how the developers setup and deployed their model into production from an engineer working on the team.https://www.kdnuggets.com/2019/07/scaling-massive-deep-learning-model-production.html
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Collaborative Evolutionary Reinforcement Learning
Intel Researchers created a new approach to RL via Collaborative Evolutionary Reinforcement Learning (CERL) that combines policy gradient and evolution methods to optimize, exploit, and explore challenges.https://www.kdnuggets.com/2019/07/collaborative-evolutionary-reinforcement-learning.html
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An Overview of Human Pose Estimation with Deep Learning
Human Pose Estimation is one of the main research areas in computer vision. The reason for its importance is the abundance of applications that can benefit from such a technology. Here's an introduction to the different techniques used in Human Pose Estimation based on Deep Learning.https://www.kdnuggets.com/2019/06/human-pose-estimation-deep-learning.html
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PySyft and the Emergence of Private Deep Learning
PySyft is an open-source framework that enables secured, private computations in deep learning, by combining federated learning and differential privacy in a single programming model integrated into different deep learning frameworks such as PyTorch, Keras or TensorFlow.https://www.kdnuggets.com/2019/06/pysyft-emergence-deep-learning.html
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The Data Fabric for Machine Learning – Part 2: Building a Knowledge-Graph
Before being able to develop a Data Fabric we need to build a Knowledge-Graph. In this article I’ll set up the basis on how to create it, in the next article we’ll go to the practice on how to do this.https://www.kdnuggets.com/2019/06/data-fabric-machine-learning-building-knowledge-graph.html
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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
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7 Steps to Mastering Data Preparation for Machine Learning with Python — 2019 Edition">7 Steps to Mastering Data Preparation for Machine Learning with Python — 2019 Edition
Interested in mastering data preparation with Python? Follow these 7 steps which cover the concepts, the individual tasks, as well as different approaches to tackling the entire process from within the Python ecosystem.https://www.kdnuggets.com/2019/06/7-steps-mastering-data-preparation-python.html
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How Google uses Reinforcement Learning to Train AI Agents in the Most Popular Sport in the World
Researchers from the Google Brain team open sourced Google Research Football, a new environment that leverages reinforcement learning to teach AI agents how to master the most popular sport in the world.https://www.kdnuggets.com/2019/06/google-reinforcement-learning-ai-agents-sport.html
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The Machine Learning Puzzle, Explained">The Machine Learning Puzzle, Explained
Lots of moving parts go into creating a machine learning model. Let's take a look at some of these core concepts and see how the machine learning puzzle comes together.https://www.kdnuggets.com/2019/06/machine-learning-puzzle-explained.html
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How to Learn Python for Data Science the Right Way">How to Learn Python for Data Science the Right Way
The biggest mistake you can make while learning Python for data science is to learn Python programming from courses meant for programmers. Avoid this mistake, and learn Python the right way by following this approach.https://www.kdnuggets.com/2019/06/python-data-science-right-way.html
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Why Machine Learning is vulnerable to adversarial attacks and how to fix it
Machine learning can process data imperceptible to humans to produce expected results. These inconceivable patterns are inherent in the data but may make models vulnerable to adversarial attacks. How can developers harness these features to not lose control of AI?https://www.kdnuggets.com/2019/06/machine-learning-adversarial-attacks.html
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Overview of Different Approaches to Deploying Machine Learning Models in Production
Learn the different methods for putting machine learning models into production, and to determine which method is best for which use case.https://www.kdnuggets.com/2019/06/approaches-deploying-machine-learning-production.html
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3 Main Approaches to Machine Learning Models
Machine learning encompasses a vast set of conceptual approaches. We classify the three main algorithmic methods based on mathematical foundations to guide your exploration for developing models.https://www.kdnuggets.com/2019/06/main-approaches-machine-learning-models.html
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What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem">What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem
We identify the 6 tools in the modern open-source Data Science ecosystem, examine the Python vs R question, and determine which tools are used the most with Deep Learning and Big Data.https://www.kdnuggets.com/2019/06/top-data-science-machine-learning-tools.html
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Using the ‘What-If Tool’ to investigate Machine Learning models
The machine learning practitioner must be a detective, and this tool from teams at Google enables you to investigate and understand your models.https://www.kdnuggets.com/2019/06/using-what-if-tool-investigate-machine-learning-models.html
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KDnuggets™ News 19:n21, Jun 5: Transitioning your Career to Data Science; 11 top Data Science, Machine Learning platforms; 7 Steps to Mastering Intermediate ML w. Python
The results of KDnuggets 20th Annual Software Poll; How to transition to a Data Science career; Mastering Intermediate Machine Learning with Python ; Understanding Natural Language Processing (NLP); Backprop as applied to LSTM, and much more.https://www.kdnuggets.com/2019/n21.html
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Top Stories, May 27 – Jun 2: A Step-by-Step Guide to Transitioning your Career to Data Science – Part 1; Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis
Understanding Backpropagation as Applied to LSTM; How the Lottery Ticket Hypothesis is Challenging Everything we Knew About Training Neural Networks; AI in the Family: how to teach machine learning to your kidshttps://www.kdnuggets.com/2019/06/top-news-week-0527-0602.html
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7 Steps to Mastering Intermediate Machine Learning with Python — 2019 Edition"> 7 Steps to Mastering Intermediate Machine Learning with Python — 2019 Edition
This is the second part of this new learning path series for mastering machine learning with Python. Check out these 7 steps to help master intermediate machine learning with Python!https://www.kdnuggets.com/2019/06/7-steps-mastering-intermediate-machine-learning-python.html
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Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis">Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis
Python continues to lead the top Data Science platforms, but R and RapidMiner hold their share; Almost 50% have used Deep Learning tools; SQL is steady; Consolidation continues.https://www.kdnuggets.com/2019/05/poll-top-data-science-machine-learning-platforms.html
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How to use continual learning in your ML models, June 19 Webinar
This webinar for professional data scientists will go over how to monitor models when in production, and how to set up automatically adaptive machine learning.https://www.kdnuggets.com/2019/05/cnvrg-io-continual-learning-ml-models.html
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Why organizations fail in scaling AI and Machine Learning
We explain why AI needs to understand business processes and how the business processes need to be able to change to bring insight from AI into the process.https://www.kdnuggets.com/2019/05/why-organizations-fail-scaling-ai-machine-learning.html
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AI in the Family: how to teach machine learning to your kids
AI is all the rage with today’s programmers, but what about the next generation? Machine learning can be introduced to young ones just now learning about code, and you can help spark their interest.https://www.kdnuggets.com/2019/05/ai-machine-learning-kids.html
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End-to-End Machine Learning: Making videos from images
Video is a natural way for us to understand three dimensional and time varying information. Read this short post on how to achieve the creation of videos from still images.https://www.kdnuggets.com/2019/05/making-videos-from-images.html
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How do you teach physics to machine learning models?
How to integrate physics-based models (these are math-based methods that explain the world around us) into machine learning models to reduce its computational complexity.https://www.kdnuggets.com/2019/05/physics-machine-learning-models.html
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The Data Fabric for Machine Learning – Part 1">The Data Fabric for Machine Learning – Part 1
How the new advances in semantics and the data fabric can help us be better at Machine Learninghttps://www.kdnuggets.com/2019/05/data-fabric-machine-learning-part-1.html
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Building Recommender systems with Azure Machine Learning service
Microsoft has provided a GitHub repository with Python best practice examples to facilitate the building and evaluation of recommendation systems using Azure Machine Learning services.https://www.kdnuggets.com/2019/05/recommender-systems-azure-machine-learning.html
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Customer Churn Prediction Using Machine Learning: Main Approaches and Models
We reach out to experts from HubSpot and ScienceSoft to discuss how SaaS companies handle the problem of customer churn prediction using Machine Learning.https://www.kdnuggets.com/2019/05/churn-prediction-machine-learning.html
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Machine Learning in Agriculture: Applications and Techniques">Machine Learning in Agriculture: Applications and Techniques
Machine Learning has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data intensive processes in agricultural operational environments.https://www.kdnuggets.com/2019/05/machine-learning-agriculture-applications-techniques.html
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How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls">How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls
We outline some of the common pitfalls of machine learning for time series forecasting, with a look at time delayed predictions, autocorrelations, stationarity, accuracy metrics, and more.https://www.kdnuggets.com/2019/05/machine-learning-time-series-forecasting.html
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Books on Graph-Powered Machine Learning, Graph Databases, Deep Learning for Search – 50% off
These 3 books will help you make the most from graph-powered databases. For a limited time, get 50% off any of them with the code kdngraph.https://www.kdnuggets.com/2019/05/manning-books-graph-machine-learning-databases.html
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“Please, explain.” Interpretability of machine learning models
Unveiling secrets of black box models is no longer a novelty but a new business requirement and we explain why using several different use cases.https://www.kdnuggets.com/2019/05/interpretability-machine-learning-models.html
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[White Paper] Unlocking the Power of Data Science & Machine Learning with Python
This guide from ActiveState provides an executive overview of how you can implement Python for your team’s data science and machine learning initiatives.https://www.kdnuggets.com/2019/05/activestate-whitepaper-data-science-machine-learning-python.html
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2019 KDnuggets Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?">2019 KDnuggets Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?
Vote in KDnuggets 20th Annual Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? We will publish the anon data, results, and trends here.https://www.kdnuggets.com/2019/05/new-poll-software-analytics-data-science-machine-learning.html
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Naive Bayes: A Baseline Model for Machine Learning Classification Performance
We can use Pandas to conduct Bayes Theorem and Scikitlearn to implement the Naive Bayes Algorithm. We take a step by step approach to understand Bayes and implementing the different options in Scikitlearn.https://www.kdnuggets.com/2019/04/naive-bayes-baseline-model-machine-learning-classification-performance.html
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The 3 Biggest Mistakes on Learning Data Science">The 3 Biggest Mistakes on Learning Data Science
Data science or whatever you want to call it is not just knowing some programming languages, math, statistics and have “domain knowledge” and here I show you why.https://www.kdnuggets.com/2019/05/biggest-mistakes-learning-data-science.html
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How to Automate Tasks on GitHub With Machine Learning for Fun and Profit
Check this tutorial on how to build a GitHub App that predicts and applies issue labels using Tensorflow and public datasets.https://www.kdnuggets.com/2019/05/automate-tasks-github-machine-learning-fun-profit.html
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Which Deep Learning Framework is Growing Fastest?
In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed?https://www.kdnuggets.com/2019/05/which-deep-learning-framework-growing-fastest.html
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Learn About Data Science & the Future of Investing from Hedge Fund Leaders at Rev 2
Rev 2 features interactive sessions, Q&A with industry luminaries, poster sessions for interesting modeling techniques and accomplishments, and stimulating conversations about how to make data science an enterprise-grade capability.https://www.kdnuggets.com/2019/04/domino-data-science-hedge-fund-rev-2.html
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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
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Machine Learning and Deep Link Graph Analytics: A Powerful Combination
We investigate how graphs can help machine learning and how they are related to deep link graph analytics for Big Data.https://www.kdnuggets.com/2019/04/machine-learning-graph-analytics.html
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How can quantum computing be useful for Machine Learning
We investigate where quantum computing and machine learning could intersect, providing plenty of use cases, examples and technical analysis.https://www.kdnuggets.com/2019/04/quantum-computing-machine-learning.html
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All you need to know about text preprocessing for NLP and Machine Learning
We present a comprehensive introduction to text preprocessing, covering the different techniques including stemming, lemmatization, noise removal, normalization, with examples and explanations into when you should use each of them.https://www.kdnuggets.com/2019/04/text-preprocessing-nlp-machine-learning.html
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Which Data Science / Machine Learning methods and algorithms did you use in 2018/2019 for a real-world application?
Which Data Science / Machine Learning methods and algorithms did you use in 2018/2019 for a real-world application? Take part in the latest KDnuggets survey and have your say.https://www.kdnuggets.com/2019/04/poll-data-science-machine-learning-methods-algorithms-use-2018-2019.html
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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
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A Beginner’s Guide to Linear Regression in Python with Scikit-Learn
What linear regression is and how it can be implemented for both two variables and multiple variables using Scikit-Learn, which is one of the most popular machine learning libraries for Python.https://www.kdnuggets.com/2019/03/beginners-guide-linear-regression-python-scikit-learn.html
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[eBook] Standardizing the Machine Learning Lifecycle
We explore what makes the machine learning lifecycle so challenging compared to regular software, and share the Databricks approach.https://www.kdnuggets.com/2019/03/databrocks-ebook-machine-learning-lifecycle.html
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Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision
In this blog, I’ll walk you through a personal project in which I cheaply built a classifier to detect anti-semitic tweets, with no public dataset available, by combining weak supervision and transfer learning.https://www.kdnuggets.com/2019/03/building-nlp-classifiers-cheaply-transfer-learning-weak-supervision.html
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My favorite mind-blowing Machine Learning/AI breakthroughs">My favorite mind-blowing Machine Learning/AI breakthroughs
We present some of our favorite breakthroughs in Machine Learning and AI in recent times, complete with papers, video links and brief summaries for each.https://www.kdnuggets.com/2019/03/favorite-ml-ai-breakthroughs.html
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[PDF] Executive Guide To Machine Learning
The Executive Guide covers the benefits to your business, the build-or-buy process, and gives a practical overview for implementing ML in your organization.https://www.kdnuggets.com/2019/03/activestate-pdf-executive-guide-machine-learning.html
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People Tracking using Deep Learning
Read this overview of people tracking and how deep learning-powered computer vision has allowed for phenomenal performance.https://www.kdnuggets.com/2019/03/people-tracking-using-deep-learning.html
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Beating the Bookies with Machine Learning
We investigate how to use a custom loss function to identify fair odds, including a detailed example using machine learning to bet on the results of a darts match and how this can assist you in beating the bookmaker.https://www.kdnuggets.com/2019/03/beating-bookies-machine-learning.html
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19 Inspiring Women in AI, Big Data, Data Science, Machine Learning">19 Inspiring Women in AI, Big Data, Data Science, Machine Learning
For the 2019 international women's day, we profile a new set of 19 inspiring women who lead the field in AI, Big Data, Data Science, and Machine Learning fields.https://www.kdnuggets.com/2019/03/women-ai-big-data-science-machine-learning.html
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Another 10 Free Must-Read Books for Machine Learning and Data Science">Another 10 Free Must-Read Books for Machine Learning and Data Science
Here's a third set of 10 free books for machine learning and data science. Have a look to see if something catches your eye, and don't forget to check the previous installments for reading material while you're here.https://www.kdnuggets.com/2019/03/another-10-free-must-read-books-for-machine-learning-and-data-science.html
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Past AI, Analytics, Big Data, Data Mining, Data Science, and Machine Learning Meetings and Conferences
2021 AI, Analytics, Big Data, Data Science, and Machine Learning meetings 2020 AI, Analytics, Big Data, Data Science, and Machine Learning meetings 2019 AI, Analytics, Read more »https://www.kdnuggets.com/meetings/past.html