Search results for deep learning

Found 2810 documents, 5922 searched:

• KDnuggets™ News 20:n36, Sep 23: New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project

  New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project; Autograd: The Best Machine Learning Library You're Not Using?; Implementing a Deep Learning Library from Scratch in Python; Online Certificates/Courses in AI, Data Science, Machine Learning; Can Neural Networks Show Imagination?

  https://www.kdnuggets.com/2020/n36.html

• KDD-2020 (virtual), the leading conference on Data Science and Knowledge Discovery, Aug 23-27 – register now

  Using an interactive VR platform, KDD-2020 brings you the latest research in AI, Data Science, Deep Learning, and Machine Learning with tutorials to improve your skills, keynotes from top experts, workshops on state-of-the-art topics and over 200 research presentations.

  https://www.kdnuggets.com/2020/08/kdd-2020-virtual-august.html

• Is depth useful for self-attention?

  Learn about recent research that is the first to explain a surprising phenomenon where in BERT/Transformer-like architectures, deepening the network does not seem to be better than widening (or, increasing the representation dimension). This empirical observation is in contrast to a fundamental premise in deep learning.

  https://www.kdnuggets.com/2020/07/depth-useful-self-attention.html

• Getting Started with TensorFlow 2">Getting Started with TensorFlow 2

  Learn about the latest version of TensorFlow with this hands-on walk-through of implementing a classification problem with deep learning, how to plot it, and how to improve its results.

  https://www.kdnuggets.com/2020/07/getting-started-tensorflow2.html

• The Most Important Fundamentals of PyTorch you Should Know">The Most Important Fundamentals of PyTorch you Should Know

  PyTorch is a constantly developing deep learning framework with many exciting additions and features. We review its basic elements and show an example of building a simple Deep Neural Network (DNN) step-by-step.

  https://www.kdnuggets.com/2020/06/fundamentals-pytorch.html

• Build Dog Breeds Classifier Step By Step with AWS Sagemaker

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

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

• Exploring the Impact of Geographic Information Systems

  GIS has mostly been behind more popular buzzwords like machine learning and deep learning. GIS has always been around us in the background being used in government, business, medicine, real estate, transport, manufacturing etc.

  https://www.kdnuggets.com/2020/04/impact-geographic-information-systems.html

• Recreating Fingerprints using Convolutional Autoencoders

  The article gets you started working with fingerprints using Deep Learning.

  https://www.kdnuggets.com/2020/03/recreating-fingerprints-using-convolutional-autoencoders.html

• Can Edge Analytics Become a Game Changer?

  Edge analytics is considered to be the future of sensor handling, and this article discusses its benefits and architecture of modern edge devices, gateways, and sensors. Deep Learning for edge analytics is also considered along with a review of experiments in human and chess figure detection using edge devices.

  https://www.kdnuggets.com/2020/02/edge-analytics-game-changer.html

• Practical Hyperparameter Optimization

  An introduction on how to fine-tune Machine and Deep Learning models using techniques such as: Random Search, Automated Hyperparameter Tuning and Artificial Neural Networks Tuning.

  https://www.kdnuggets.com/2020/02/practical-hyperparameter-optimization.html

• Disentangling disentanglement: Ideas from NeurIPS 2019

  This year’s NEURIPS-2019 Vancouver conference recently concluded and featured a dozen papers on disentanglement in deep learning. What is this idea and why is it so interesting in machine learning? This summary of these papers will give you initial insight in disentanglement as well as ideas on what you can explore next.

  https://www.kdnuggets.com/2020/01/disentangling-disentanglement-neurips-2019.html

• Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models

  The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.

  https://www.kdnuggets.com/2019/12/google-open-sources-mobilenetv3-improve-mobile-computer-vision-models.html

• Three Methods of Data Pre-Processing for Text Classification

  This blog shows how text data representations can be used to build a classifier to predict a developer’s deep learning framework of choice based on the code that they wrote, via examples of TensorFlow and PyTorch projects.

  https://www.kdnuggets.com/2019/11/ibm-data-preprocessing-text-classification.html

• Generalization in Neural Networks

  When training a neural network in deep learning, its performance on processing new data is key. Improving the model's ability to generalize relies on preventing overfitting using these important methods.

  https://www.kdnuggets.com/2019/11/generalization-neural-networks.html

• Research Guide for Transformers

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

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

• Convolutional Neural Network for Breast Cancer Classification

  See how Deep Learning can help in solving one of the most commonly diagnosed cancer in women.

  https://www.kdnuggets.com/2019/10/convolutional-neural-network-breast-cancer-classification.html

• Using Neural Networks to Design Neural Networks: The Definitive Guide to Understand Neural Architecture Search

  A recent survey outlined the main neural architecture search methods used to automate the design of deep learning systems.

  https://www.kdnuggets.com/2019/10/using-neural-networks-design-neural-networks-definitive-guide-understand-neural-architecture-search.html

• A 2019 Guide for Automatic Speech Recognition

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

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

• TensorFlow vs PyTorch vs Keras for NLP">TensorFlow vs PyTorch vs Keras for NLP

  These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.

  https://www.kdnuggets.com/2019/09/tensorflow-pytorch-keras-nlp.html

• 9 Tips For Training Lightning-Fast Neural Networks In Pytorch

  Who is this guide for? Anyone working on non-trivial deep learning models in Pytorch such as industrial researchers, Ph.D. students, academics, etc. The models we're talking about here might be taking you multiple days to train or even weeks or months.

  https://www.kdnuggets.com/2019/08/9-tips-training-lightning-fast-neural-networks-pytorch.html

• This New Google Technique Help Us Understand How Neural Networks are Thinking">This New Google Technique Help Us Understand How Neural Networks are Thinking

  Recently, researchers from the Google Brain team published a paper proposing a new method called Concept Activation Vectors (CAVs) that takes a new angle to the interpretability of deep learning models.

  https://www.kdnuggets.com/2019/07/google-technique-understand-neural-networks-thinking.html

• Building a Recommender System, Part 2

  This post explores an technique for collaborative filtering which uses latent factor models, a which naturally generalizes to deep learning approaches. Our approach will be implemented using Tensorflow and Keras.

  https://www.kdnuggets.com/2019/07/building-recommender-system-part-2.html

• 10 Gradient Descent Optimisation Algorithms + Cheat Sheet

  Gradient descent is an optimization algorithm used for minimizing the cost function in various ML algorithms. Here are some common gradient descent optimisation algorithms used in the popular deep learning frameworks such as TensorFlow and Keras.

  https://www.kdnuggets.com/2019/06/gradient-descent-algorithms-cheat-sheet.html

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

  Fastai offers some really good courses in machine learning and deep learning for programmers. I recently took their "Practical Deep Learning for Coders" course and found it really interesting. Here are my learnings from the course.

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

• How to Automate Hyperparameter Optimization

  A step-by-step guide into performing a hyperparameter optimization task on a deep learning model by employing Bayesian Optimization that uses the Gaussian Process. We used the gp_minimize package provided by the Scikit-Optimize (skopt) library to perform this task.

  https://www.kdnuggets.com/2019/06/automate-hyperparameter-optimization.html

• Probability Mass and Density Functions

  This content is part of a series about the chapter 3 on probability from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016). It aims to provide intuitions/drawings/python code on mathematical theories and is constructed as my understanding of these concepts.

  https://www.kdnuggets.com/2019/05/probability-mass-density-functions.html

• Data Science with Optimus Part 1: Intro

  With Optimus you can clean your data, prepare it, analyze it, create profilers and plots, and perform machine learning and deep learning, all in a distributed fashion, because on the back-end we have Spark, TensorFlow, Sparkling Water and Keras. It’s super easy to use.

  https://www.kdnuggets.com/2019/04/data-science-with-optimus-part-1-intro.html

• Towards Automatic Text Summarization: Extractive Methods

  The basic idea looks simple: find the gist, cut off all opinions and detail, and write a couple of perfect sentences, the task inevitably ended up in toil and turmoil. Here is a short overview of traditional approaches that have beaten a path to advanced deep learning techniques.

  https://www.kdnuggets.com/2019/03/towards-automatic-text-summarization.html

• How to do Everything in Computer Vision

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

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

• How to Engineer Your Way Out of Slow Models

  We describe how we handle performance issues with our deep learning models, including how to find subgraphs that take a lot of calculation time and how to extract these into a caching mechanism.

  https://www.kdnuggets.com/2018/11/engineer-slow-models.html

• An Introduction to AI">An Introduction to AI

  We provide an introduction to AI key terminologies and methodologies, covering both Machine Learning and Deep Learning, with an extensive list including Narrow AI, Super Intelligence, Classic Artificial Intelligence, and more.

  https://www.kdnuggets.com/2018/11/an-introduction-ai.html

• Latest Trends in Computer Vision Technology and Applications

  We investigate the advancements in deep learning, the rise of edge computing, object recognition with point cloud, VR and AR enhanced merged reality, semantic instance segmentation and more.

  https://www.kdnuggets.com/2018/11/trends-computer-vision-technology-applications.html

• The Most in Demand Skills for Data Scientists">The Most in Demand Skills for Data Scientists

  Data scientists are expected to know a lot — machine learning, computer science, statistics, mathematics, data visualization, communication, and deep learning. How should data scientists who want to be in demand by employers spend their learning budget?

  https://www.kdnuggets.com/2018/11/most-demand-skills-data-scientists.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

• Understand Why ODSC is the Most Recommended Conference for Applied Data Science

  Running 4 days, 40 training sessions, 50 workshops, and over 200 speakers, an ODSC conference offers unparalleled depth and breadth in deep learning, machine learning, and other data science topics. Save 20% offer ends tomorrow. Register now!

  https://www.kdnuggets.com/2018/10/odsc-understand-most-recommended-conference-applied-data-science.html

• Data Augmentation For Bounding Boxes: Rethinking image transforms for object detection

  Data Augmentation is one way to battle this shortage of data, by artificially augmenting our dataset. In fact, the technique has proven to be so successful that it's become a staple of deep learning systems.

  https://www.kdnuggets.com/2018/09/data-augmentation-bounding-boxes-image-transforms.html

• How GOAT Taught a Machine to Love Sneakers

  Embeddings are a fantastic tool to create reusable value with inherent properties similar to how humans interpret objects. GOAT uses deep learning to generate these for their entire sneaker catalogue.

  https://www.kdnuggets.com/2018/08/goat-taught-machine-love-sneakers.html

• Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV">Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV

  For the data scientist within you let's use this opportunity to do some analysis on soccer clips. With the use of deep learning and opencv we can extract interesting insights from video clips

  https://www.kdnuggets.com/2018/07/analyze-soccer-game-using-tensorflow-object-detection-opencv.html

• Building a Basic Keras Neural Network Sequential Model

  The approach basically coincides with Chollet's Keras 4 step workflow, which he outlines in his book "Deep Learning with Python," using the MNIST dataset, and the model built is a Sequential network of Dense layers. A building block for additional posts.

  https://www.kdnuggets.com/2018/06/basic-keras-neural-network-sequential-model.html

• The Keras 4 Step Workflow">The Keras 4 Step Workflow

  In his book "Deep Learning with Python," Francois Chollet outlines a process for developing neural networks with Keras in 4 steps. Let's take a look at this process with a simple example.

  https://www.kdnuggets.com/2018/06/keras-4-step-workflow.html

• Boost your data science skills. Learn linear algebra.">Boost your data science skills. Learn linear algebra.

  The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning. Acquiring these skills can boost your ability to understand and apply various data science algorithms.

  https://www.kdnuggets.com/2018/05/boost-data-science-skills-learn-linear-algebra.html

• KDnuggets™ News 18:n18, May 2: Blockchain Explained in 7 Python Functions; Data Science Dirty Secret; Choosing the Right Evaluation Metric

  Also: Building Convolutional Neural Network using NumPy from Scratch; Data Science Interview Guide; Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model; Jupyter Notebook for Beginners: A Tutorial

  https://www.kdnuggets.com/2018/n18.html

• Getting Started with PyTorch Part 1: Understanding How Automatic Differentiation Works

  PyTorch has emerged as a major contender in the race to be the king of deep learning frameworks. What makes it really luring is it’s dynamic computation graph paradigm.

  https://www.kdnuggets.com/2018/04/getting-started-pytorch-understanding-automatic-differentiation.html

• Visual Aesthetics: Judging photo quality using AI techniques

  We built a deep learning system that can automatically analyze and score an image for aesthetic quality with high accuracy. Check the demo and see your photo measures up!

  https://www.kdnuggets.com/2018/01/visual-aesthetics-photo-quality-ai.html

• How (and Why) to Create a Good Validation Set

  The definitions of training, validation, and test sets can be fairly nuanced, and the terms are sometimes inconsistently used. In the deep learning community, “test-time inference” is often used to refer to evaluating on data in production, which is not the technical definition of a test set.

  https://www.kdnuggets.com/2017/11/create-good-validation-set.html

• Tensorflow Tutorial, Part 2 – Getting Started

  This tutorial will lay a solid foundation to your understanding of Tensorflow, the leading Deep Learning platform. The second part shows how to get started, install, and build a small test case.

  https://www.kdnuggets.com/2017/09/tensorflow-tutorial-part-2.html

• Mind Reading: Using Artificial Neural Nets to Predict Viewed Image Categories From EEG Readings

  This post outlines the approach taken at a recent deep learning hackathon, hosted by YCombinator-backed startup DeepGram. The dataset: EEG readings from a Stanford research project that predicted which category of images their test subjects were viewing using linear discriminant analysis.

  https://www.kdnuggets.com/2017/08/mind-reading-using-artificial-neural-nets.html

• Visualizing Convolutional Neural Networks with Open-source Picasso

  Toolkits for standard neural network visualizations exist, along with tools for monitoring the training process, but are often tied to the deep learning framework. Could a general, easy-to-setup tool for generating standard visualizations provide a sanity check on the learning process?

  https://www.kdnuggets.com/2017/08/visualizing-convolutional-neural-networks-open-source-picasso.html

• ResNets, HighwayNets, and DenseNets, Oh My!

  This post walks through the logic behind three recent deep learning architectures: ResNet, HighwayNet, and DenseNet. Each make it more possible to successfully trainable deep networks by overcoming the limitations of traditional network design.

  https://www.kdnuggets.com/2016/12/resnets-highwaynets-densenets-oh-my.html

• Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017">Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017

  Key themes included the polling failures in 2016 US Elections, Deep Learning, IoT, greater focus on value and ROI, and increasing adoption of predictive analytics by the "masses" of industry.
   
  

  https://www.kdnuggets.com/2016/12/data-science-predictive-analytics-main-developments-trends.html

• R, Python Duel As Top Analytics, Data Science software – KDnuggets 2016 Software Poll Results

  R remains the leading tool, with 49% share, but Python grows faster and almost catches up to R. RapidMiner remains the most popular general Data Science platform. Big Data tools used by almost 40%, and Deep Learning usage doubles.

  https://www.kdnuggets.com/2016/06/r-python-top-analytics-data-mining-data-science-software.html

• New KDnuggets Tutorials Page: Learn R, Python, Data Visualization, Data Science, and more

  Introducing new KDnuggets Tutorials page with useful resources for learning about Business Analytics, Big Data, Data Science, Data Mining, R, Python, Data Visualization, Spark, Deep Learning and more.

  https://www.kdnuggets.com/2016/03/new-tutorials-section-r-python-data-visualization-data-science.html

• MetaMind Mastermind Richard Socher: Uncut Interview

  In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.

  https://www.kdnuggets.com/2015/10/metamind-mastermind-richard-socher-deep-learning-interview.html

• Data is Ugly – Tales of Data Cleaning

  Whether you want to do business analytics or build the deep learning models, getting correct data and cleansing it appropriately remains the major task. Find out experts opinions on how you can make efficient data cleansing and collection efforts.

  https://www.kdnuggets.com/2015/08/data-ugly-tales-data-cleaning.html

• TheWalnut.io: An Easy Way to Create Algorithm Visualizations

  Google's DeepDream project has gone viral which allows to visualize the deep learning neural networks. It highlights a need for a generalized algorithm visualization tool, in this post we introduce to you one such effort.

  https://www.kdnuggets.com/2015/07/thewalnutio-algorithm-visualizations.html

• Most Viewed Big Data Videos on YouTube

  The top Big Data YouTube videos by those like Hortonworks and Kirk D. Borne cover diverse topics including Hadoop, Big Data Trends, Deep Learning, and Big Data Leadership.

  https://www.kdnuggets.com/2015/05/most-viewed-big-data-videos-youtube.html

• The Inconvenient Truth About Data Science

  Data is never clean, you will spend most of your time cleaning and preparing data, 95% of tasks do not require deep learning, and more inconvenient wisdom.

  https://www.kdnuggets.com/2015/05/data-science-inconvenient-truth.html

• Top KDnuggets tweets, Sep 19-21: Dilbert funniest cartoons on #BigData, data mining; Guess which pattern is random

  Guess which pattern is random, which machine-generated? Dilbert 20 funniest cartoons on #BigData, data mining, privacy; Data Scientist Cartoon; Neural Networks and Deep Learning, free online book (draft).

  https://www.kdnuggets.com/2014/09/top-tweets-sep19-21.html

• The Ultimate Roadmap to Becoming Specialised in The Tech Industry

  There is more than one route that you can take to be a competitive tech professional.

  https://www.kdnuggets.com/the-ultimate-roadmap-to-becoming-specialised-in-the-tech-industry

• 5 AI Courses From Google to Advance Your Career

  Start your AI journey today with these courses from Google.

  https://www.kdnuggets.com/5-ai-courses-from-google-to-advance-your-career

• The 8 AI Search Engines That You Should Replace Google With

  GenAI has enabled new search engine platforms with unique features and advantages, challenging Google's dominance.

  https://www.kdnuggets.com/top-8-ai-search-engine-that-you-should-replace-with-google

• Top Free Data Science Online Courses for 2024

  Learn data science in 2024 for FREE with these online courses.

  https://www.kdnuggets.com/top-free-data-science-online-courses-for-2024

• Build An AI Application with Python in 10 Easy Steps

  Explore the fundamental steps for creating a successful AI Application with Python and other tools.

  https://www.kdnuggets.com/build-an-ai-application-with-python-in-10-easy-steps

• 5 Data Science Communities to Advance Your Career

  The best way to improve our knowledge is by learning together with communities.

  https://www.kdnuggets.com/5-data-science-communities-to-advance-your-career

• Data Science and the Go Programming Language

  Northwestern’s School of Professional Studies uses Go in Its Master of Science in Data Science Program.

  https://www.kdnuggets.com/2024/03/nwu-data-science-go-programming-language

• Unlock the Secrets of LLMs in 60-Minute with Andrej Karpathy

  Karpathy's talk provides a comprehensive yet accessible introduction to large language models, explaining their capabilities, future potential, and associated security risks in an engaging manner.

  https://www.kdnuggets.com/unlock-the-secrets-of-llms-in-a-60-minute-with-andrej-karpathy

• 5 Courses to Master LLMs

  The future world is full of LLM, and you don’t want to miss this most sought skill.

  https://www.kdnuggets.com/5-courses-to-master-llms

• Top 5 Linux Distro for Data Science

  If you are considering transitioning from Microsoft Windows to another operating system that suits your needs, check out these five Linux distributions for data science and machine learning.

  https://www.kdnuggets.com/top-5-linux-distro-for-data-science

• Top 6 YouTube Series for Data Science Beginners

  Want to start your data science journey from home, for free, and work at your own pace? Have a dive into this data science roadmap using the YouTube series.

  https://www.kdnuggets.com/top-6-youtube-series-for-data-science-beginners

• 3 Inspirational Stories of Leaders in AI

  Every leader has their origin story, and here are some that might inspire you.

  https://www.kdnuggets.com/3-inspirational-stories-of-leaders-in-ai

• Large Language Models Explained in 3 Levels of Difficulty

  Simple explanations, no matter what your level is right now.

  https://www.kdnuggets.com/large-language-models-explained-in-3-levels-of-difficulty

• Top 5 DataCamp Courses for Mastering Generative AI

  Learn the skills you require to kickstart your Generative AI journey with DataCamp - beginner, intermediate, and expert!

  https://www.kdnuggets.com/top-5-datacamp-courses-for-mastering-generative-ai

• 2024 Tech Trends: AI Breakthroughs & Development Insights from O’Reilly’s Free Report

  Want to prepare your tech career for 2024 and onwards? Have a look at O’Reilly’s FREE technology trends report.

  https://www.kdnuggets.com/2024-tech-trends-ai-breakthroughs-development-insights-oreilly-free-report

• 5 FREE Courses on AI and ChatGPT to Take You From 0-100

  Want to learn more about AI and ChatGPT in 2024 for FREE? Keep reading.

  https://www.kdnuggets.com/5-free-courses-on-ai-and-chatgpt-to-take-you-from-0-100

• Books, Courses, and Live Events to Learn Generative AI with O’Reilly

  If you are new to generative AI or an expert who wants to learn more, O’Reilly offers a range of resources to kickstart your generative AI journey.

  https://www.kdnuggets.com/books-courses-and-live-events-to-learn-generative-ai-with-oreilly

• Why LLMs Used Alone Can’t Address Your Company’s Predictive Needs

  LLMs aren't the right tool for most business applications. Find out why — and learn which AI techniques are a better match.

  https://www.kdnuggets.com/2024/01/pecan-llms-used-alone-cant-address-companys-predictive-needs

• Natural Language Processing: Bridging Human Communication with AI

  The post highlights real-world examples of NLP use cases across industries. It also covers NLP's objectives, challenges, and latest research developments.

  https://www.kdnuggets.com/natural-language-processing-bridging-human-communication-with-ai

• Learn with LinkedIn: Free Courses About AI

  Want to learn about AI? You can for FREE with LinkedIn.

  https://www.kdnuggets.com/learn-with-linkedin-free-courses-about-ai

• AI Prompt Engineers are Making $300k/y

  Prompt engineering and generative AI are becoming hotter by the day. Be part of the heat!

  https://www.kdnuggets.com/ai-prompt-engineers-are-making-300ky

• 3 Crucial Challenges in Conversational AI Development and How to Avoid Them

  Developing a conversational AI chatbot requires substantial effort. However, understanding and addressing key challenges in natural language understanding can streamline the development process.

  https://www.kdnuggets.com/3-crucial-challenges-in-conversational-ai-development-and-how-to-avoid-them

• Are We Undervaluing Simple Models?

  Never underestimate any algorithms that we can use.

  https://www.kdnuggets.com/are-we-undervaluing-simple-models

• 4 Steps to Become a Generative AI Developer

  In this post, we will cover what a generative AI developer does, what tools you need to master, and how to get started.

  https://www.kdnuggets.com/4-steps-to-become-a-generative-ai-developer

• Level 50 Data Scientist: Python Libraries to Know

  This article will help you understand the different tools of Data Science used by experts for Data Visualization, Model Building, and Data Manipulation.

  https://www.kdnuggets.com/level-50-data-scientist-python-libraries-to-know

• What Junior ML Engineers Actually Need to Know to Get Hired?

  This article will provided you with a better understanding of what skills are required for a junior ML developer to be considered for a job. If you are looking to land your first job, you should read this article thoroughly.

  https://www.kdnuggets.com/what-junior-ml-engineers-actually-need-to-know-to-get-hired

• Back to Basics Pathway

  Kickstart your 2024 with KDnuggets Back to Basics Data Science pathway!

  https://www.kdnuggets.com/back-to-basics-pathway

• Evaluating Methods for Calculating Document Similarity

  The blog covers methods for representing documents as vectors and computing similarity, such as Jaccard similarity, Euclidean distance, cosine similarity, and cosine similarity with TF-IDF, along with pre-processing steps for text data, such as tokenization, lowercasing, removing punctuation, removing stop words, and lemmatization.

  https://www.kdnuggets.com/evaluating-methods-for-calculating-document-similarity

• The Best Data Science Resources, Bootcamp, and Courses to Learn Data Science in the New Year

  We've partnered with Springboard, the leading data science bootcamp offering personalized 1:1 mentorship, dedicated career support, proven outcomes, and an unbeatable money-back job guarantee, to present a handpicked collection of resources to supercharge your data science journey in the coming year.

  https://www.kdnuggets.com/2023/12/springboard-best-data-science-resources-bootcamp-courses-learn-data-science-new-year

• 5 Cheap Books to Master Data Science

  There are many data-learning materials locked up behind expensive books. These cheap books would bolster your skills without blowing up your savings.

  https://www.kdnuggets.com/5-cheap-books-to-master-data-science

• 5 Use Cases of DALLE-3

  Learn how you can use DALL-E 3 to make your life a little bit easier (or a lot).

  https://www.kdnuggets.com/5-use-cases-of-dalle-3

• 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

• Generative AI Key Terms Explained

  This article introduces and explains key terms important to generative AI, and links to additional resources to learn more.

  https://www.kdnuggets.com/generative-ai-key-terms-explained

• The Top 5 Alternatives to GitHub for Data Science Projects

  The blog discusses five platforms designed for data scientists with specialized capabilities in managing large datasets, models, workflows, and collaboration beyond what GitHub offers.

  https://www.kdnuggets.com/the-top-5-alternatives-to-github-for-data-science-projects

• Learn Probability in Computer Science with Stanford University for FREE

  Probability is one of the foundational elements of computer science. Some bootcamps will skim over the topic, however, it is integral to your computer science knowledge.

  https://www.kdnuggets.com/learn-probability-in-computer-science-with-stanford-university-for-free

• Beyond Human Boundaries: The Rise of SuperIntelligence

  From ANI to AGI and Beyond: Deciphering AI's Evolutionary Path.

  https://www.kdnuggets.com/beyond-human-boundaries-the-rise-of-superintelligence

• Back to Basics Week 4: Advanced Topics and Deployment

  Welcome back to Week 4 of KDnuggets’ "Back to Basics" series. This week, we will dive into more advanced topics such as neural networks and deployment.

  https://www.kdnuggets.com/back-to-basics-week-4-advanced-topics-and-deployment

• A Comprehensive List of Resources to Master Large Language Models

  Large Language Models (LLMs) have now become an integral part of various applications. This article provides an extensive list of resources for anyone interested to dive into the world of LLMs.

  https://www.kdnuggets.com/a-comprehensive-list-of-resources-to-master-large-language-models

• Job Trends in Data Analytics: Part 2

  Check out these skillsets in demand for the data analytics job market.

  https://www.kdnuggets.com/job-trends-in-data-analytics-part-2

• The Rise and Fall of Prompt Engineering: Fad or Future?

  This article provides an overview of prompt engineering, from its inception to current status.

  https://www.kdnuggets.com/the-rise-and-fall-of-prompt-engineering-fad-or-future

• 7 Steps to Running a Small Language Model on a Local CPU

  Discover how to run a small language model on your local CPU in just seven easy steps.

  https://www.kdnuggets.com/7-steps-to-running-a-small-language-model-on-a-local-cpu

• 5 Free Courses to Master Data Science

  Want to break into data science? Start upskilling today with these free courses to learn programming, data analysis, and machine learning.

  https://www.kdnuggets.com/5-free-courses-to-master-data-science

• 365 Data Science Offers Free Course Access Until Nov. 20

  From November 6 (07:00 PST) to November 20 (07:00 PST), enjoy free unlimited access to 365 Data Science's comprehensive curriculum, interactive courses, practical data projects, and earn industry-recognized certificates—all at no charge.

  https://www.kdnuggets.com/2023/11/365datascience-offers-free-course-access-nov-20

• 5 Free University Courses on Data Analytics

  Thinking about getting into the data analytical world but do not know where to start? Have a look at these 5 FREE university courses on data analytics.

  https://www.kdnuggets.com/5-free-university-courses-on-data-analytics

• Back to Basics Week 1: Python Programming & Data Science Foundations

  Cultivate your data science expertise with KDnuggets' Back to Basics pathway, which includes Python, data manipulation, and visualization.

  https://www.kdnuggets.com/back-to-basics-week-1-python-programming-data-science-foundations

• Dive into the Future with Kaggle’s AI Report 2023 – See What’s Hot

  Dive into the world's largest data science and machine learning community on what they have learnt about the world of AI.

  https://www.kdnuggets.com/dive-into-the-future-with-kaggle-ai-report-2023-see-what-hot

• 5 Simple Steps Series: Master Python, SQL, Scikit-learn, PyTorch & Google Cloud

  Dive into KDnuggets Back to Basics: Getting Started in 5 Steps series to help you master Python, SQL, Scikit-learn, PyTorch, and Google Cloud Platform.

  https://www.kdnuggets.com/5-simple-steps-series-master-python-sql-scikit-learn-pytorch-google-cloud

• Top 10 AI Startups to Work for in India

  Want to jumpstart your career in AI? Discover the top 10 trailblazing Indian startups that are reshaping industries with cutting-edge innovation and providing unparalleled opportunities to work on impactful projects.

  https://www.kdnuggets.com/top-10-ai-startups-to-work-for-in-india

• Future-Proof Your Data Game: Top Skills Every Data Scientist Needs in 2023

  An overview of the most sought-after skills in 2023 based on the rise of generative AI.

  https://www.kdnuggets.com/futureproof-your-data-game-top-skills-every-data-scientist-needs-in-2023

• Drag, Drop, Analyze: The Rise of No-Code Data Science

  No-code or low-code functionalities in data science have gained significant traction in recent years. These solutions are well-proven and matured, and they make data science more accessible to a wider range of people.

  https://www.kdnuggets.com/drag-drop-analyze-the-rise-of-nocode-data-science

• Greening AI: 7 Strategies to Make Applications More Sustainable

  The article delves into a comprehensive methodology that sheds light on how to accurately estimate the carbon footprint associated with AI applications. It explains the environmental impact of AI, a crucial consideration in today's world.

  https://www.kdnuggets.com/greening-ai-7-strategies-to-make-applications-more-sustainable

• A Brief History of the Neural Networks

  From the biological neuron to LLMs: How AI became smart.

  https://www.kdnuggets.com/a-brief-history-of-the-neural-networks

• Gradient Descent: The Mountain Trekker’s Guide to Optimization with Mathematics

  Gradient descent is an optimization technique used to minimise errors in machine learning models. By iteratively adjusting parameters in the steepest direction of decrease, it seeks the lowest error value.

  https://www.kdnuggets.com/gradient-descent-the-mountain-trekker-guide-to-optimization-with-mathematics

• 7 Steps to Mastering Large Language Models (LLMs)

  Large Language Models (LLMs) have unlocked a new era in natural language processing. So why not learn more about them? Go from learning what large language models are to building and deploying LLM apps in 7 easy steps with this guide.

  https://www.kdnuggets.com/7-steps-to-mastering-large-language-models-llms

• Elevate Your Search Engine Skills with Uplimit’s Search with ML Course!

  Elevate Your Search Engine Skills! Join Uplimit's SearchML Course now for a 4-week deep dive into machine learning and search. Boost rankings, enhance retrieval, and build with OpenSearch. Enroll today and level up with expert guidance!

  https://www.kdnuggets.com/2023/10/uplimit-elevate-your-search-engine-skills-search-with-ml-course

• 3 Data Science Projects Guaranteed to Land You That Job

  Imagine you’re allowed to do only three data science projects. Which should you choose to guarantee you get the job? Here’s my choice!

  https://www.kdnuggets.com/3-data-science-projects-guaranteed-to-land-you-that-job

• How Close Are We to AGI?

  Will AI be able to surpass human intelligence? An article going through the current progression, and challenges of AGI.

  https://www.kdnuggets.com/how-close-are-we-to-agi

• 7 Steps to Mastering Natural Language Processing

  Want to learn all about Natural Language Processing (NLP)? Here is a 7 step guide to help you go from the fundamentals of machine learning and Python to Transformers, recent advances in NLP, and beyond.

  https://www.kdnuggets.com/7-steps-to-mastering-natural-language-processing

• Job Trends in Data Analytics: NLP for Job Trend Analysis

  Perform job trend analysis and check the results using NLP.

  https://www.kdnuggets.com/job-trends-in-data-analytics-nlp-for-job-trend-analysis

• Getting Started with PyTorch in 5 Steps

  This tutorial provides an in-depth introduction to machine learning using PyTorch and its high-level wrapper, PyTorch Lightning. The article covers essential steps from installation to advanced topics, offering a hands-on approach to building and training neural networks, and emphasizing the benefits of using Lightning.

  https://www.kdnuggets.com/5-steps-getting-started-pytorch

• Top 7 Free Cloud Notebooks for Data Science

  Cloud notebooks are game-changers for data science, providing free access to computing, pre-built environments, collaboration features, and third-party integrations - everything you need to enhance your workflow.

  https://www.kdnuggets.com/top-7-free-cloud-notebooks-for-data-science

• Diving into the Pool: Unraveling the Magic of CNN Pooling Layers

  A Beginner's Guide to Max, Average, and Global Pooling in Convolutional Neural Networks.

  https://www.kdnuggets.com/diving-into-the-pool-unraveling-the-magic-of-cnn-pooling-layers

• 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

• Building a Convolutional Neural Network with PyTorch

  This blog post provides a tutorial on constructing a convolutional neural network for image classification in PyTorch, leveraging convolutional and pooling layers for feature extraction as well as fully-connected layers for prediction.

  https://www.kdnuggets.com/building-a-convolutional-neural-network-with-pytorch

• 30 Years of Data Science: A Review From a Data Science Practitioner

  A review from a data science practitioner.

  https://www.kdnuggets.com/30-years-of-data-science-a-review-from-a-data-science-practitioner

• Exploring Neural Networks

  Unlocking the power of AI: a suide to neural networks and their applications.

  https://www.kdnuggets.com/exploring-neural-networks

• How Generative AI is disrupting data practices

  The release of Language Learning Model (LLM) ChatGPT by OpenAI in November of last year opened the floodgates leading to alternatives including Google Bard and Microsoft Bing and Gen AI has proved massively disruptive, with businesses seeking to explore how they can apply the technology.

  https://www.kdnuggets.com/2023/09/reed-generative-ai-disrupting-data-practices

• Don’t Miss Out! Enroll in FREE Courses Before 2023 Ends

  Complete the last quarter of the year and improve your skills to get you kickstarted for 2024’s self-development plan with these FREE courses.

  https://www.kdnuggets.com/dont-miss-out-enroll-in-free-courses-before-2023-ends

• Unveiling Neural Magic: A Dive into Activation Functions

  Cracking the code of activation functions: Demystifying their purpose, selection, and timing.

  https://www.kdnuggets.com/unveiling-neural-magic-a-dive-into-activation-functions

• Getting Started with Scikit-learn in 5 Steps

  This tutorial offers a comprehensive hands-on walkthrough of machine learning with Scikit-learn. Readers will learn key concepts and techniques including data preprocessing, model training and evaluation, hyperparameter tuning, and compiling ensemble models for enhanced performance.

  https://www.kdnuggets.com/5-steps-getting-started-scikit-learn

• The 5 Best AI Tools For Maximizing Productivity

  KDnuggets reviews a diverse set of 5 AI tools to help maximize your productivity. Have a look and see what our recommendations include.

  https://www.kdnuggets.com/the-5-best-ai-tools-for-maximizing-productivity

• Linear Regression from Scratch with NumPy

  Mastering the Basics of Linear Regression and Fundamentals of Gradient Descent and Loss Minimization.

  https://www.kdnuggets.com/linear-regression-from-scratch-with-numpy