Search results for Long Short Term Memory Network Development Programming

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• Ten Years of AI in Review

  From image classification to chatbot therapy.

  https://www.kdnuggets.com/2023/06/ten-years-ai-review.html

• AgentGPT: Autonomous AI Agents in your Browser

  Give your AI agent a name and goal, and watch it accomplish the assigned objective.

  https://www.kdnuggets.com/2023/06/agentgpt-autonomous-ai-agents-browser.html

• DataLang: A New Programming Language for Data Scientists… Created by ChatGPT?

  I recently tasked ChatGPT-4's to come up with a new programming language appropriate for data scientists in their day to day tasks. Let's look at the results, and the process of getting there.

  https://www.kdnuggets.com/2023/04/datalang-new-programming-language-data-scientists-chatgpt.html

• 7 Best Libraries for Machine Learning Explained

  Learn about machine learning libraries for building and deploying machine learning models.

  https://www.kdnuggets.com/2023/01/7-best-libraries-machine-learning-explained.html

• Data Science, Statistics and Machine Learning Dictionary

  Check out this curated list of the most used data science terminology and get a leg up on your learning.

  https://www.kdnuggets.com/2022/05/data-science-statistics-machine-learning-dictionary.html

• Awesome list of datasets in 100+ categories

  With an estimated 44 zettabytes of data in existence in our digital world today and approximately 2.5 quintillion bytes of new data generated daily, there is a lot of data out there you could tap into for your data science projects. It's pretty hard to curate through such a massive universe of data, but this collection is a great start. Here, you can find data from cancer genomes to UFO reports, as well as years of air quality data to 200,000 jokes. Dive into this ocean of data to explore as you learn how to apply data science techniques or leverage your expertise to discover something new.

  https://www.kdnuggets.com/2021/05/awesome-list-datasets.html

• Machine learning adversarial attacks are a ticking time bomb

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

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

• Powerful CSV processing with kdb+

  This article provides a glimpse into the available tools to work with CSV files and describes how kdb+ and its query language q raise CSV processing to a new level of performance and simplicity.

  https://www.kdnuggets.com/2020/07/powerful-csv-processing-kdb.html

• Deep Learning in Finance: Is This The Future of the Financial Industry?

  Get a handle on how deep learning is affecting the finance industry, and identify resources to further this understanding and increase your knowledge of the various aspects.

  https://www.kdnuggets.com/2020/07/deep-learning-finance-future-financial-industry.html

• Complex logic at breakneck speed: Try Julia for data science

  We show a comparative performance benchmarking of Julia with an equivalent Python code to show why Julia is great for data science and machine learning.

  https://www.kdnuggets.com/2020/05/complex-logic-breakneck-speed-julia-data-science.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

• Graph Machine Learning Meets UX: An uncharted love affair

  When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.

  https://www.kdnuggets.com/2020/01/graph-machine-learning-ux.html

• A Comprehensive Guide to Natural Language Generation

  Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.

  https://www.kdnuggets.com/2020/01/guide-natural-language-generation.html

• Enabling the Deep Learning Revolution

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

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

• 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

• Understanding Tensor Processing Units

  The Tensor Processing Unit (TPU) is Google's custom tool to accelerate machine learning workloads using the TensorFlow framework. Learn more about what TPUs do and how they can work for you.

  https://www.kdnuggets.com/2019/07/understanding-tensor-processing-units.html

• Understanding Backpropagation as Applied to LSTM

  Backpropagation is one of those topics that seem to confuse many once you move past feed-forward neural networks and progress to convolutional and recurrent neural networks. This article gives you and overall process to understanding back propagation by giving you the underlying principles of backpropagation.

  https://www.kdnuggets.com/2019/05/understanding-backpropagation-applied-lstm.html

• Data-science? Agile? Cycles? My method for managing data-science projects in the Hi-tech industry.

  The following is a method I developed, which is based on my personal experience managing a data-science-research team and was tested with multiple projects. In the next sections, I’ll review the different types of research from a time point-of-view, compare development and research workflow approaches and finally suggest my work methodology.

  https://www.kdnuggets.com/2019/02/data-science-agile-cycles-method-managing-projects-hi-tech-industry.html

• DevOps for Data Scientists: Taming the Unicorn

  How do we version control the model and add it to an app? How will people interact with our website based on the outcome? How will it scale!?

  https://www.kdnuggets.com/2018/07/devops-data-scientists-taming-unicorn.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

• Artificial Intelligence and Speech Recognition for Chatbots: A Primer

  Bot bots bots... Read this overview of how artificial intelligence and natural language processing are contributing to chatbot development, and where it all goes from here.

  https://www.kdnuggets.com/2017/01/artificial-intelligence-speech-recognition-chatbots-primer.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

• 35 Open Source tools for Internet of Things

  If you have heard about the Internet of Things many times by now, its time to join the conversation. Explore the many open source tools & projects related to Internet of Things.

  https://www.kdnuggets.com/2016/07/open-source-tools-internet-things.html

• Spark SQL for Real-Time Analytics

  Apache Spark is the hottest topic in Big Data. This tutorial discusses why Spark SQL is becoming the preferred method for Real Time Analytics and for next frontier, IoT (Internet of Things).

  https://www.kdnuggets.com/2015/09/spark-sql-real-time-analytics.html