Search results for Natural Language Processing

Found 1057 documents, 5985 searched:

• The Art of Data Science: The Skills You Need and How to Get Them

  Learn, how to turn the deluge of data into the gold by algorithms, feature engineering, reasoning out business value and ultimately building a data driven organization.

  https://www.kdnuggets.com/2015/12/art-data-science-skills.html

• Top 10 Machine Learning Projects on Github">Top 10 Machine Learning Projects on Github

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

  https://www.kdnuggets.com/2015/12/top-10-machine-learning-github.html

• 50 Useful Machine Learning & Prediction APIs

  We present a list of 50 APIs selected from areas like machine learning, prediction, text analytics & classification, face recognition, language translation etc. Start consuming APIs!

  https://www.kdnuggets.com/2015/12/machine-learning-data-science-apis.html

• Sentiment Analysis 101

  Sentiment analysis can be incredibly useful, and can help companies better answer pertinent questions and gain valuable business insights. Sentiment analysis technologies will continue to improve as they become more widely adopted. But what can sentiment analysis do for you?

  https://www.kdnuggets.com/2015/12/sentiment-analysis-101.html

• Deep Learning for Visual Question Answering

  Here we discuss about the Visual Question Answering problem, and I’ll also present neural network based approaches for same.

  https://www.kdnuggets.com/2015/11/deep-learning-visual-question-answering.html

• Understanding Convolutional Neural Networks for NLP

  Dive into the world of Convolution Neural Networks (CNN), learn how they work, how to apply them for NLP, and how to tune CNN hyperparameters for best performance.

  https://www.kdnuggets.com/2015/11/understanding-convolutional-neural-networks-nlp.html

• Why Deep Learning Works – Key Insights and Saddle Points

  A quality discussion on the theoretical motivations for deep learning, including distributed representation, deep architecture, and the easily escapable saddle point.

  https://www.kdnuggets.com/2015/11/theoretical-deep-learning.html

• How Data Science increased the profitability of the e-commerce industry?

  Data Science helps businesses provide a richer understanding of the customers by capturing and integrating the information on customers web behaviour, their life events, what led to the purchase of a product or service, how customers interact with different channels, and more.

  https://www.kdnuggets.com/2015/11/how-data-science-increased-profitability-e-commerce-industry.html

• SentimentBuilder: Visual Analysis of Unstructured Texts

  Sankey diagrams are mainly used to visualize the flow of data on energy flows, material flow and trade-offs. SentimentBuilder found how to use them with unstructured text in their online NLP tool.

  https://www.kdnuggets.com/2015/09/sentimentbuilder-free-online-natural-language-processing-tool.html

• 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more

  Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science.

  https://www.kdnuggets.com/2015/09/free-data-science-books.html

• Understanding Basic Concepts and Dispersion

  In analytics it is a common practice to understand the basic statistical properties of its variables viz. range, mean and deviation. Centrality measures are the most important to them, explore how to use these measures.

  https://www.kdnuggets.com/2015/08/statistics-understanding-basic-concepts-dispersion.html

• Cognitive Computing: Solving the Big Data Problem?

  With a shortage of data scientists, what are the alternatives for making sense of Big Data? We examine Cognitive Computing, its strengths, and how it can fit into the current Big Data landscape.

  https://www.kdnuggets.com/2015/06/cognitive-computing-solving-big-data-problem.html

• Top 20 Python Machine Learning Open Source Projects

  We examine top Python Machine learning open source projects on Github, both in terms of contributors and commits, and identify most popular and most active ones.

  https://www.kdnuggets.com/2015/06/top-20-python-machine-learning-open-source-projects.html

• Deep Learning, The Curse of Dimensionality, and Autoencoders

  Autoencoders are an extremely exciting new approach to unsupervised learning and for many machine learning tasks they have already surpassed the decades of progress made by researchers handpicking features.

  https://www.kdnuggets.com/2015/03/deep-learning-curse-dimensionality-autoencoders.html

• KDnuggets™ News 14:n28, Oct 29

  Features | Software | Opinions | Reports | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets | CFP Read more »

  https://www.kdnuggets.com/2014/n28.html

• KDnuggets™ News 14:n26, Oct 8

  Features | Software | Opinions | Interviews | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets | CFP Read more »

  https://www.kdnuggets.com/2014/n26.html

• When Watson Meets Machine Learning

  Our report on a recent Cognitive Systems meetup co-sponsored by IBM Watson and NYU Center for Data Science, IBM Watson Ecosystem, and machine learning applications, from healthcare to cognitive toys. You will want Fang!

  https://www.kdnuggets.com/2014/07/watson-meets-machine-learning.html

• Interview: Samaneh Moghaddam, Applied Researcher, eBay on Opinion Mining – Typical Projects and Major Challenges

  We discuss typical sentiment analysis problems at eBay, underrated challenges, career motivation, important soft skills and more.

  https://www.kdnuggets.com/2014/06/interview-samaneh-moghaddam-ebay-projects-challenges.html

• KDnuggets™ News 14:n15, Jun 18

  Features (6) | Software (3) | Opinions (6) | News (2) | Webcasts (1) | Courses (1) | Jobs (7) | Academic (1) | Publications Read more »

  https://www.kdnuggets.com/2014/n15.html

• KDnuggets™ News 14:n14, Jun 10

  Features (8) | Software (3) | Opinions (14) | News (6) | Webcasts (3) | Courses (1) | Meetings and Reports (9) | Jobs (6) Read more »

  https://www.kdnuggets.com/2014/n14.html

• KDnuggets™ News 14:n10, Apr 30

  Features (9) | Opinions (5) | Software (3) | News (6) | Webcasts (1) | Courses (3) | Meetings (4) | Jobs (10) | Academic Read more »

  https://www.kdnuggets.com/2014/n10.html

• KDnuggets™ News 14:n06, Mar 19

  Features (11) | News (3) | Software (6) | Webcasts (3) | Courses (5) | Competitions (3) | Meetings (6) | Jobs (3) | Academic Read more »

  https://www.kdnuggets.com/2014/n06.html

• KDnuggets™ News 14:n04, Feb 19

  Features (7) | News (10) | Software (2) | Webcasts (2) | Courses (2) | Meetings (2) | Jobs (10) | Academic (4) | Publications Read more »

  https://www.kdnuggets.com/2014/n04.html

• KDnuggets™ News 14:n01, Jan 8

  coming on Jan 8

  https://www.kdnuggets.com/2014/n01.html

• 2013 Dec Courses and Events: Analytics, Big Data, Data Mining and Data Science

  All (95) | News, Software (27) | Courses, Events (12) | Jobs | Academic | Publications (38) Replay: What Lies Ahead for Big Data and Read more »

  https://www.kdnuggets.com/2013/12/courses-events.html

• 2013 Dec: Analytics, Big Data, Data Mining and Data Science News

  All (95) | News, Software (27) | Courses, Events (12) | Jobs | Academic | Publications (38) Unicorn Data Scientists vs Data Science Teams - Read more »

  https://www.kdnuggets.com/2013/12/index.html

• Are there programming frameworks for web content mining?

  Bing Liu answers: Although many Web content mining problems have the same framework of extraction and integration, the current techniques for dealing with them are Read more »

  https://www.kdnuggets.com/faq/web-mining-frameworks.html

• AI, Analytics, Data Science, and Machine Learning websites

  A B C D E F G H I J K L M N O P Q R S T U V W XYZ AAAI Read more »

  https://www.kdnuggets.com/websites/sites.html

• Blogs on AI, Analytics, Data Science, Machine Learning

  Here are some of the most interesting and regularly-updated blogs on Analytics, Big Data, Data Science, Data Mining, and Machine Learning, in alphabetical order. Blog Read more »

  https://www.kdnuggets.com/websites/blogs.html

• KDnuggets™ News 13:n30, Dec 11

  Features (12) | Software (2) | Webcasts (1) | Courses, Events (5) | Meetings (1) | Jobs (5) | Academic (1) | Competitions (1) | Publications Read more »

  https://www.kdnuggets.com/2013/n30.html

• Mikut Data Mining Tools Big List – Update

  An update of the Excel table describing 325 recent and historical data mining tools is now online (Excel format), 31 of them were added since the last update in November 2012. These new updated tools include new published tools and some well-established tools with a statistical background.

  https://www.kdnuggets.com/2013/09/mikut-data-mining-tools-big-list-update.html

• KDnuggets™ News 13:n23, Sep 24

  Features (8) | Software (3) | Webcasts (2) | Courses, Events (4) | Meetings (3) | Jobs (10) | Academic (3) | Competitions (1) | Publications Read more »

  https://www.kdnuggets.com/2013/n23.html

• KDnuggets™ News 13:n16, Jul 3

  Features (7) | Software (1) | Webcasts (1) | Courses, Events (2) | Meetings (2) | Jobs (13) | Academic (1) | Publications (4) | Tweets Read more »

  https://www.kdnuggets.com/2013/n16.html

• Text Analysis, Text Mining, and Information Retrieval Software

  http likes 47 Commercial | online | free On-line Text Mining / Text Analytics Tools Ranks.nl, keyword analysis and webmaster tools. Text Sentiment Visualizer (online), Read more »

  https://www.kdnuggets.com/software/text.html

• Companies with Analytics, Data Mining, Data Science, and Machine Learning Products

  A B C D E F G H I J K L M N O P Q R S T U V W XYZ Advanced Read more »

  https://www.kdnuggets.com/companies/products.html

• Consulting Companies in AI, Analytics, Data Science, and Machine Learning

  A B C D E F G H I J K L M N O P Q R S T U V W XYZ 4i, Read more »

  https://www.kdnuggets.com/companies/consulting.html

• KDnuggets™ News 13:n13, May 22

  Features (11) | Software (1) | Webcasts (4) | Courses, Events (2) | Jobs (11) | Academic (1) | Competitions (3) | Publications (5) | Tweets Read more »

  https://www.kdnuggets.com/2013/n13.html

• Mastering Python: 7 Strategies for Writing Clear, Organized, and Efficient Code

  Optimize Your Python Workflow: Proven Techniques for Crafting Production-Ready Code

  https://www.kdnuggets.com/mastering-python-7-strategies-for-writing-clear-organized-and-efficient-code

• A Starter Guide to Data Structures for AI and Machine Learning

  This article is an overview of a particular subset of data structures useful in machine learning and AI development, along with explanations and example implementations.

  https://www.kdnuggets.com/guide-data-structures-ai-and-machine-learning

• OpenAI API for Beginners: Your Easy-to-Follow Starter Guide

  Learn how to use OpenAI Python API for accessing language, embedding, audio, vision, and image generation models.

  https://www.kdnuggets.com/openai-api-for-beginners-your-easy-to-follow-starter-guide

• Maximizing Efficiency in Data Analysis with ChatGPT

  This article has provided a brief overview of ChatGPT and its capabilities. It also discussed the importance of efficient data analysis and the benefits of integrating it into the analysis process.

  https://www.kdnuggets.com/maximizing-efficiency-in-data-analysis-with-chatgpt

• Prompt Engineering 101: Mastering Effective LLM Communication

  This article serves as an introduction to those looking to understanding what prompt engineering is, and to learn more about some of the most important techniques currently used in the discipline.

  https://www.kdnuggets.com/prompt-engineering-101-mastering-effective-llm-communication

• Free Harvard Course: Introduction to AI with Python

  Looking for a great course to learn Artificial Intelligence with Python? Check out this free course from Harvard University.

  https://www.kdnuggets.com/free-harvard-course-introduction-to-ai-with-python

• Mastering Data Science Workflows with ChatGPT

  This article highlights the skills data scientists can learn to make the most use of the prowess of ChatGPT.

  https://www.kdnuggets.com/mastering-data-science-workflows-with-chatgpt

• Getting Started with Claude 2 API

  I recently gained access to Anthropic's API, and I am impressed by how easy it is to use and faster than OpenAI API.

  https://www.kdnuggets.com/getting-started-with-claude-2-api

• Mastering the Data Universe: Key Steps to a Thriving Data Science Career

  This article covered the six main pillars of a data science career from learning skills to getting a job.

  https://www.kdnuggets.com/mastering-the-data-universe-key-steps-to-a-thriving-data-science-career

• The Data Maturity Pyramid: From Reporting to a Proactive Intelligent Data Platform

  This article describes the data maturity pyramid and its various levels, from simple reporting to AI-ready data platforms. It emphasizes the importance of data for business and illustrates how data platforms serve as the driving force behind AI.

  https://www.kdnuggets.com/the-data-maturity-pyramid-from-reporting-to-a-proactive-intelligent-data-platform

• Want to Become a Data Scientist? Part 1: 10 Hard Skills You Need

  A quick 10-step hard skill guide on what you need to become a Data Scientist.

  https://www.kdnuggets.com/want-to-become-a-data-scientist-part-1-10-hard-skills-you-need

• LangChain + Streamlit + Llama: Bringing Conversational AI to Your Local Machine

  Integrating Open Source LLMs and LangChain for Free Generative Question Answering (No API Key required).

  https://www.kdnuggets.com/2023/08/langchain-streamlit-llama-bringing-conversational-ai-local-machine.html

• ChatGPT Code Interpreter: Do Data Science in Minutes

  This new ChatGPT plugin can analyze data, write Python code, and build machine-learning models.

  https://www.kdnuggets.com/2023/07/chatgpt-code-interpreter-data-science-minutes.html

• Geocoding for Data Scientists

  This article introduces geocoding as part of a data science pipeline. It covers manual and API based geocoding with a fun and engaging example.

  https://www.kdnuggets.com/2023/06/geocoding-data-scientists.html

• Data Analytics Tools You Need To Know in 2023

  What tools do you need to know to be a successful data analyst?

  https://www.kdnuggets.com/2023/05/data-analytics-tools-need-know-2023.html

• What Is ChatGPT Doing and Why Does It Work?

  In this article, we will explain how ChatGPT works and why it is able to produce coherent and diverse conversations.

  https://www.kdnuggets.com/2023/04/chatgpt-work.html

• GPT-4: Everything You Need To Know

  A new model by OpenAI with improved natural language generation and understanding capabilities.

  https://www.kdnuggets.com/2023/03/gpt4-everything-need-know.html

• New ChatGPT and Whisper APIs from OpenAI

  A quick overview of ChatGPT and Whisper models API.

  https://www.kdnuggets.com/2023/03/new-chatgpt-whisper-apis-openai.html

• Simple NLP Pipelines with HuggingFace Transformers

  Transformers by HuggingFace is an all-encompassing library with state-of-the-art pre-trained models and easy-to-use tools.

  https://www.kdnuggets.com/2023/02/simple-nlp-pipelines-huggingface-transformers.html

• ChatGPT: Everything You Need to Know

  All you need to know about ChatGPT: what it can do, how it works, and its limitations.

  https://www.kdnuggets.com/2023/01/chatgpt-everything-need-know.html

• Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science

  Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.

  https://www.kdnuggets.com/2020/10/data-science-minimum-10-essential-skills.html

• The Gap Between Deep Learning and Human Cognitive Abilities

  How do we bridge this gap between deep learning and human cognitive ability?

  https://www.kdnuggets.com/2022/10/gap-deep-learning-human-cognitive-abilities.html

• Converting Text Documents to Token Counts with CountVectorizer

  The post explains the significance of CountVectorizer and demonstrates its implementation with Python code.

  https://www.kdnuggets.com/2022/10/converting-text-documents-token-counts-countvectorizer.html

• 3 Simple Ways to Speed Up Your Python Code

  The post explains three popular frameworks, PySpark, Dask, and Ray, and discusses various factors to select the most appropriate one for your project.

  https://www.kdnuggets.com/2022/10/3-simple-ways-speed-python-code.html

• 7 Tips for Python Beginners

  Learn useful tips to start your career as a Python developer.

  https://www.kdnuggets.com/2022/09/7-tips-python-beginners.html

• Data-Centric AI: The Latest Research You Need to Know

  While a vast majority of research efforts today are preoccupied solely with ML models and algorithms, the data itself tends to be secondary and is treated as fixed. This claim is potentially detrimental.

  https://www.kdnuggets.com/2022/02/datacentric-ai-latest-research-need-know.html

• What Is the Difference Between SQL and Object-Relational Mapping (ORM)?

  Object-relational mapping, or ORM, is a technique that allows you to interact with databases using the object-oriented paradigm of the programming language of your choosing. How is that different from structured query language, though, and when do you use them?

  https://www.kdnuggets.com/2022/02/difference-sql-object-relational-mapping-orm.html

• 5 Ways to Apply AI to Small Data Sets

  It is better to use AI algorithms on small data sets for results free of human errors and false results when applied correctly. Here are some methods to apply AI to small data sets.

  https://www.kdnuggets.com/2022/02/5-ways-apply-ai-small-data-sets.html

• Artificial Intelligence and the Metaverse

  For those of you who don’t know, Artificial intelligence (AI) is the ability of a computer or a computer-controlled robot to perform tasks that are usually done by humans as they require human intelligence. Metaverse’s AI research and usage include content analysis, supervised speech processing, computer vision, and much more. 

  https://www.kdnuggets.com/2022/02/artificial-intelligence-metaverse.html

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

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

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

• KDnuggets: Personal History and Nuggets of Experience

  After 28+ years of publishing and editing KDnuggets, I am retiring and transitioning KDnuggets to Matthew Mayo, who will become the new editor-in-chief. I want to share with you my story of KDnuggets and highlight some of the useful nuggets of experience I learned along this amazing journey.

  https://www.kdnuggets.com/2021/11/kdnuggets-history.html

• Build a Serverless News Data Pipeline using ML on AWS Cloud

  This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.

  https://www.kdnuggets.com/2021/11/build-serverless-news-data-pipeline-ml-aws-cloud.html

• The Evolution of Tokenization – Byte Pair Encoding in NLP

  Though we have SOTA algorithms for tokenization, it's always a good practice to understand the evolution trail and learning how have we reached here. Read this introduction to Byte Pair Encoding.

  https://www.kdnuggets.com/2021/10/evolution-tokenization-byte-pair-encoding-nlp.html

• Data science SQL interview questions from top tech firms">Data science SQL interview questions from top tech firms

  As a data scientist, there is one thing you really need to understand and know how to handle: data. With SQL being a foundational technical approach for working with data, it should not be surprising that the top tech companies will ask about your SQL skills during an interview. Here, we cover the key concepts tested so you can best prepare for your next data science interview.

  https://www.kdnuggets.com/2021/10/data-science-sql-interview-questions.html

• DeepMind’s New Super Model: Perceiver IO is a Transformer that can Handle Any Dataset

  The new transformer-based architecture can process audio, video and images using a single model.

  https://www.kdnuggets.com/2021/08/deepmind-new-super-model-perceiver-io-transformer.html

• GPU-Powered Data Science (NOT Deep Learning) with RAPIDS">GPU-Powered Data Science (NOT Deep Learning) with RAPIDS

  How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.

  https://www.kdnuggets.com/2021/08/gpu-powered-data-science-deep-learning-rapids.html

• Why and how should you learn “Productive Data Science”?">Why and how should you learn “Productive Data Science”?

  What is Productive Data Science and what are some of its components?

  https://www.kdnuggets.com/2021/07/learn-productive-data-science.html

• How to Create Unbiased Machine Learning Models

  In this post we discuss the concepts of bias and fairness in the Machine Learning world, and show how ML biases often reflect existing biases in society. Additionally, We discuss various methods for testing and enforcing fairness in ML models.

  https://www.kdnuggets.com/2021/07/create-unbiased-machine-learning-models.html

• Geometric foundations of Deep Learning">Geometric foundations of Deep Learning

  Geometric Deep Learning is an attempt for geometric unification of a broad class of machine learning problems from the perspectives of symmetry and invariance. These principles not only underlie the breakthrough performance of convolutional neural networks and the recent success of graph neural networks but also provide a principled way to construct new types of problem-specific inductive biases.

  https://www.kdnuggets.com/2021/07/geometric-foundations-deep-learning.html

• A Graph-based Text Similarity Method with Named Entity Information in NLP

  In this article, the author summarizes the 2017 paper "A Graph-based Text Similarity Measure That Employs Named Entity Information" as per their understanding. Better understand the concepts by reading along.

  https://www.kdnuggets.com/2021/06/graph-based-text-similarity-method-named-entity-information-nlp.html

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

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

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

• Software Engineering Best Practices for Data Scientists

  This is a crash course on how to bridge the gap between data science and software engineering.

  https://www.kdnuggets.com/2021/03/software-engineering-best-practices-data-scientists.html

• The Ultimate Guide to Acing Coding Interviews for Data Scientists">The Ultimate Guide to Acing Coding Interviews for Data Scientists

  This article covers understanding the 4 types of coding interview questions and preparing for them effectively.

  https://www.kdnuggets.com/2021/03/ultimate-guide-acing-coding-interviews-data-scientists.html

• Machine learning is going real-time

  Extracting immediate predictions from machine learning algorithms on the spot based on brand-new data can offer a next level of interaction and potential value to its consumers. The infrastructure and tech stack required to implement such real-time systems is also next level, and many organizations -- especially in the US -- seem to be resisting. But, what even is real-time ML, and how can it deliver a better experience?

  https://www.kdnuggets.com/2021/01/machine-learning-real-time.html

• Attention mechanism in Deep Learning, Explained

  Attention is a powerful mechanism developed to enhance the performance of the Encoder-Decoder architecture on neural network-based machine translation tasks. Learn more about how this process works and how to implement the approach into your work.

  https://www.kdnuggets.com/2021/01/attention-mechanism-deep-learning-explained.html

• Data scientist or machine learning engineer? Which is a better career option?

  In order to build automated data processing systems, we require professionals like Machine Learning Engineers and Data Scientists. But which of these is a better career option right now? Read on to find out.

  https://www.kdnuggets.com/2020/11/greatlearning-data-scientist-machine-learning-engineer.html

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

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

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

• AI Papers to Read in 2020

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

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

• 4 Tricks to Effectively Use JSON in Python

  Working with JSON in Python is a breeze, this will get you started right away.

  https://www.kdnuggets.com/2020/09/4-tricks-effectively-use-json-python.html

• Explainable and Reproducible Machine Learning Model Development with DALEX and Neptune

  With ML models serving real people, misclassified cases (which are a natural consequence of using ML) are affecting peoples’ lives and sometimes treating them very unfairly. It makes the ability to explain your models’ predictions a requirement rather than just a nice to have.

  https://www.kdnuggets.com/2020/08/explainable-reproducible-machine-learning-model-development-dalex-neptune.html

• Data Science Meets Devops: MLOps with Jupyter, Git, and Kubernetes

  An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow.

  https://www.kdnuggets.com/2020/08/data-science-meets-devops-mlops-jupyter-git-kubernetes.html

• Introduction to Federated Learning">Introduction to Federated Learning

  Federated learning means enabling on-device training, model personalization, and more. Read more about it in this article.

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

• Top 6 Reasons Data Scientists Should Know Java

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

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

• Peer Reviewing Data Science Projects">Peer Reviewing Data Science Projects

  In any technical development field, having other practitioners review your work before shipping code off to production is a valuable support tool to make sure your work is error-proof. Even through your preparation for the review, improvements might be discovered and then other issues that escaped your awareness can be spotted by outsiders. This peer scrutiny can also be applied to Data Science, and this article outlines a process that you can experiment with in your team.

  https://www.kdnuggets.com/2020/04/peer-reviewing-data-science-projects.html

• Python for data analysis… is it really that simple?!?">Python for data analysis… is it really that simple?!?

  The article addresses a simple data analytics problem, comparing a Python and Pandas solution to an R solution (using plyr, dplyr, and data.table), as well as kdb+ and BigQuery solutions. Performance improvement tricks for these solutions are then covered, as are parallel/cluster computing approaches and their limitations.

  https://www.kdnuggets.com/2020/04/python-data-analysis-really-that-simple.html

• 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

• Artificial Intelligence: Salaries Heading Skyward

  While the average salary for a Software Engineer is around $100,000 to $150,000, to make the big bucks you want to be an AI or Machine Learning (Specialist/Scientist/Engineer.)

  https://www.kdnuggets.com/2019/10/artificial-intelligence-salaries-heading-skyward.html

• 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

• Build Your First Voice Assistant

  Hone your practical speech recognition application skills with this overview of building a voice assistant using Python.

  https://www.kdnuggets.com/2019/09/build-your-first-voice-assistant.html

• An Overview of Topics Extraction in Python with Latent Dirichlet Allocation

  A recurring subject in NLP is to understand large corpus of texts through topics extraction. Whether you analyze users’ online reviews, products’ descriptions, or text entered in search bars, understanding key topics will always come in handy.

  https://www.kdnuggets.com/2019/09/overview-topics-extraction-python-latent-dirichlet-allocation.html

• How to count Big Data: Probabilistic data structures and algorithms

  Learn how probabilistic data structures and algorithms can be used for cardinality estimation in Big Data streams.

  https://www.kdnuggets.com/2019/08/count-big-data-probabilistic-data-structures-algorithms.html

• 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

• 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

• XGBoost Algorithm: Long May She Reign

  In recent years, XGBoost algorithm has gained enormous popularity in academic as well as business world. We outline some of the reasons behind this incredible success.

  https://www.kdnuggets.com/2019/05/xgboost-algorithm.html

• 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

• Distributed Artificial Intelligence: A primer on Multi-Agent Systems, Agent-Based Modeling, and Swarm Intelligence

  Distributed Artificial Intelligence (DAI) is a class of technologies and methods that span from swarm intelligence to multi-agent technologies. It is one of the subsets of AI where simulation has greater importance that point-prediction.

  https://www.kdnuggets.com/2019/04/distributed-artificial-intelligence-multi-agent-systems-agent-based-modeling-swarm-intelligence.html

• 3 Reasons Why AutoML Won’t Replace Data Scientists Yet

  We dispel the myth that AutoML is replacing Data Scientists jobs by highlighting three factors in Data Science development that AutoML can’t solve.

  https://www.kdnuggets.com/2019/03/why-automl-wont-replace-data-scientists.html

• Data Science Project Flow for Startups

  The aim of this post, then, is to present the characteristic project flow that I have identified in the working process of both my colleagues and myself in recent years. Hopefully, this can help both data scientists and the people working with them to structure data science projects in a way that reflects their uniqueness.

  https://www.kdnuggets.com/2019/01/data-science-project-flow-startups.html

• Practical Apache Spark in 10 Minutes

  Check out this series of articles on Apache Spark. Each part is a 10 minute tutorial on a particular Apache Spark topic. Read on to get up to speed using Spark.

  https://www.kdnuggets.com/2019/01/practical-apache-spark-10-minutes.html

• Multi-Class Text Classification with Doc2Vec & Logistic Regression

  Doc2vec is an NLP tool for representing documents as a vector and is a generalizing of the word2vec method. In order to understand doc2vec, it is advisable to understand word2vec approach.

  https://www.kdnuggets.com/2018/11/multi-class-text-classification-doc2vec-logistic-regression.html

• Building a Question-Answering System from Scratch

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

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

• Sequence Modeling with Neural Networks – Part I

  In the context of this post, we will focus on modeling sequences as a well-known data structure and will study its specific learning framework.

  https://www.kdnuggets.com/2018/10/sequence-modeling-neural-networks-part-1.html

• Emotion and Sentiment Analysis: A Practitioner’s Guide to NLP

  Sentiment analysis is widely used, especially as a part of social media analysis for any domain, be it a business, a recent movie, or a product launch, to understand its reception by the people and what they think of it based on their opinions or, you guessed it, sentiment!

  https://www.kdnuggets.com/2018/08/emotion-sentiment-analysis-practitioners-guide-nlp-5.html

• Named Entity Recognition: A Practitioner’s Guide to NLP

  Named entity recognition (NER) , also known as entity chunking/extraction , is a popular technique used in information extraction to identify and segment the named entities and classify or categorize them under various predefined classes.

  https://www.kdnuggets.com/2018/08/named-entity-recognition-practitioners-guide-nlp-4.html

• A Beginner’s Guide to the Data Science Pipeline">A Beginner’s Guide to the Data Science Pipeline

  On one end was a pipe with an entrance and at the other end an exit. The pipe was also labeled with five distinct letters: "O.S.E.M.N."

  https://www.kdnuggets.com/2018/05/beginners-guide-data-science-pipeline.html

• Implementing Deep Learning Methods and Feature Engineering for Text Data: FastText

  Overall, FastText is a framework for learning word representations and also performing robust, fast and accurate text classification. The framework is open-sourced by Facebook on GitHub.

  https://www.kdnuggets.com/2018/05/implementing-deep-learning-methods-feature-engineering-text-data-fasttext.html

• Data Science Interview Guide

  Traditionally, Data Science would focus on mathematics, computer science and domain expertise. While I will briefly cover some computer science fundamentals, the bulk of this blog will mostly cover the mathematical basics one might either need to brush up on (or even take an entire course).

  https://www.kdnuggets.com/2018/04/data-science-interview-guide.html

• Ranking Popular Distributed Computing Packages for Data Science

  We examined 140 frameworks and distributed programing packages and came up with a list of top 20 distributed computing packages useful for Data Science, based on a combination of Github, Stack Overflow, and Google results.

  https://www.kdnuggets.com/2018/03/top-distributed-computing-packages-data-science.html

• Four Big Data Trends for 2018

  Curious about the future of Big Data and AI? Here’s what the trends have it in 2018 for innovations.

  https://www.kdnuggets.com/2018/01/four-big-data-trends-2018.html

• Simple Ways Of Working With Medium To Big Data Locally

  An overview of the installation and implementation of simple techniques for working with large datasets in your machine.

  https://www.kdnuggets.com/2017/12/simple-medium-big-data-locally.html

• Deep Learning Made Easy with Deep Cognition

  So normally we do Deep Learning programming, and learning new APIs, some harder than others, some are really easy an expressive like Keras, but how about a visual API to create and deploy Deep Learning solutions with the click of a button? This is the promise of Deep Cognition.

  https://www.kdnuggets.com/2017/12/deep-learning-made-easy-deep-cognition.html

• Big Data: Main Developments in 2017 and Key Trends in 2018">Big Data: Main Developments in 2017 and Key Trends in 2018

  As we bid farewell to one year and look to ring in another, KDnuggets has solicited opinions from numerous Big Data experts as to the most important developments of 2017 and their 2018 key trend predictions.

  https://www.kdnuggets.com/2017/12/big-data-main-developments-2017-key-trends-2018.html

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

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

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

• How To Write Better SQL Queries: The Definitive Guide – Part 1

  Most forget that SQL isn’t just about writing queries, which is just the first step down the road. Ensuring that queries are performant or that they fit the context that you’re working in is a whole other thing. This SQL tutorial will provide you with a small peek at some steps that you can go through to evaluate your query.

  https://www.kdnuggets.com/2017/08/write-better-sql-queries-definitive-guide-part-1.html

• Using AI to Super Compress Images

  Neural Network algorithms are showing promising results for different complex problems. Here we discuss how these algorithms are used in image compression.

  https://www.kdnuggets.com/2017/08/ai-compress-images.html

• First Steps of Learning Deep Learning: Image Classification in Keras

  Whether you want to start learning deep learning for you career, to have a nice adventure (e.g. with detecting huggable objects) or to get insight into machines before they take over, this post is for you!

  https://www.kdnuggets.com/2017/08/first-steps-learning-deep-learning-image-classification-keras.html

• How I Used Deep Learning To Train A Chatbot To Talk Like Me">How I Used Deep Learning To Train A Chatbot To Talk Like Me

  In this post, we’ll be looking at how we can use a deep learning model to train a chatbot on my past social media conversations in hope of getting the chatbot to respond to messages the way that I would.

  https://www.kdnuggets.com/2017/08/deep-learning-train-chatbot-talk-like-me.html

• 42 Essential Quotes by Data Science Thought Leaders

  42 illuminating quotes you need to read if you’re a data scientist or considering a career in the field – insights from industry experts tackling the tough questions that every data scientist faces.

  https://www.kdnuggets.com/2017/05/42-essential-quotes-data-science-thought-leaders.html

• Neuroscience for Data Scientists: Understanding Human Behaviour

  Neuroscience is very complex and advanced study of brain and people often misuse this term. Here we try to explain neuroscience terminologies and use of data science for such studies.

  https://www.kdnuggets.com/2017/03/neuroscience-data-science-human-behaviour.html

• 6 areas of AI and Machine Learning to watch closely">6 areas of AI and Machine Learning to watch closely

  Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward.

  https://www.kdnuggets.com/2017/01/6-areas-ai-machine-learning.html

• Why the Data Scientist and Data Engineer Need to Understand Virtualization in the Cloud

  This article covers the value of understanding the virtualization constructs for the data scientist and data engineer as they deploy their analysis onto all kinds of cloud platforms. Virtualization is a key enabling layer of software for these data workers to be aware of and to achieve optimal results from.

  https://www.kdnuggets.com/2017/01/data-scientist-engineer-understand-virtualization-cloud.html

• 50+ Data Science, Machine Learning Cheat Sheets, updated">50+ Data Science, Machine Learning Cheat Sheets, updated

  Gear up to speed and have concepts and commands handy in Data Science, Data Mining, and Machine learning algorithms with these cheat sheets covering R, Python, Django, MySQL, SQL, Hadoop, Apache Spark, Matlab, and Java.

  https://www.kdnuggets.com/2016/12/data-science-machine-learning-cheat-sheets-updated.html

• Deep Learning Reading Group: Skip-Thought Vectors

  Skip-thought vectors take inspiration from Word2Vec skip-gram and attempt to extend it to sentences, and are created using an encoder-decoder model. Read on for an overview of the paper.

  https://www.kdnuggets.com/2016/11/deep-learning-group-skip-thought-vectors.html