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An effective way of reducing the dimensionality of your data
Shikhar Gupta
https://towardsdatascience.com/understanding-locality-sensitive-hashing-49f6d1f6134 | Locality Sensitive Hashing | [
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Logistic Regression is one of the basic and popular algorithm to solve a classification problem. It
Sarang Narkhede
https://towardsdatascience.com/understanding-logistic-regression-9b02c2aec102 | Understanding Logistic Regression | [
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In my previous post on model interpretability, I provided an overview of common techniques used to investigate machine learning models. In this blog post, I will provide a more thorough explanation of LIME.
Lars Hulstaert
https://towardsdatascience.com/understanding-model-predictions-with-lime-a582fdff3a3b | Understanding model predictions with LIME | [
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Hi Folks, thank you for your claps on my all previous blogs, which really encourages me to write
Madhav Mishra
https://towardsdatascience.com/understanding-panel-data-regression-c24cd6c5151e | Understanding Panel Data Regression | [
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Image Recognition has advanced in recent years due to availability of large datasets and powerful GPUs
John Olafenwa
https://towardsdatascience.com/understanding-residual-networks-9add4b664b03 | UNDERSTANDING RESIDUAL NETWORKS | [
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SettingWithCopyWarning is one of the most common hurdles people run into when learning pandas
Benjamin Pryke
https://towardsdatascience.com/understanding-settingwithcopywarning-7142952a01fa | Understanding SettingWithCopyWarning | [
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In a perfect world, data scientists would take subjectivity out of their conclusions
KaylaMatthews
https://towardsdatascience.com/understanding-subjectivity-in-data-science-70a25b2ea39f | Understanding Subjectivity in Data Science | [
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Hi folks, I hope you all are doing well. In this blog let us elaborate Central Limit Theorem (CLT). As on a normal front any book would state CLT in Statistics as,
Madhav Mishra
https://towardsdatascience.com/understanding-the-central-limit-theorem-642473c63ad8 | Understanding The Central Limit Theorem | [
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Ive observed that just like me, a lot of us who try to learn about support vector machines find it difficult to comprehend the brilliance of kernels. It took me quite some time and a lot of resources but Ive finally crossed the river and I intend to help you folks do that
Harish Kandan
https://towardsdatascience.com/un... | Understanding the kernel trick. | [
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The importance of using the right metrics
William Koehrsen
https://towardsdatascience.com/unintended-consequences-and-goodharts-law-68d60a94705c | Unintended Consequences and Goodharts Law | [
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Unsupervised Learning is a class of Machine Learning techniques to find the patterns in data. The
Vihar Kurama
https://towardsdatascience.com/unsupervised-learning-with-python-173c51dc7f03 | Unsupervised Learning with Python | [
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If youve heard about the transposed convolution and got confused what it actually means
Naoki Shibuya
https://towardsdatascience.com/up-sampling-with-transposed-convolution-9ae4f2df52d0 | Up-sampling with Transposed Convolution | [
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Ive been a long time user of Dublin Bikes since I came here over 5 years ago, and like
James
https://towardsdatascience.com/usage-patterns-of-dublin-bikes-stations-484bdd9c5b9e | Usage patterns of Dublin Bikes stations | [
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Up-selling and cross-selling
Ryan Aminollahi
https://towardsdatascience.com/use-algorithms-to-recommend-items-to-customers-in-python-347b769b21f3 | Use Algorithms to Recommend Items to Customers in Python | [
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Serialization and Easier Cross-validation
Ceshine Lee
https://towardsdatascience.com/use-torchtext-to-load-nlp-datasets-part-ii-f146c8b9a496 | Use torchtext to Load NLP DatasetsPart II | [
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Recipes for overcoming the users push-back once you start
Maksym Zavershynskyi
https://towardsdatascience.com/user-experience-with-machine-learning-3bcb90fa88a0 | User Experience with Machine Learning | [
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There are several time-series forecasting techniques like auto regression (AR) models, moving
Ravindra Kompella
https://towardsdatascience.com/using-lstms-to-forecast-time-series-4ab688386b1f | Using LSTMs to forecast time-series | [
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The code in this post is also available as a
Yvo Keuter
https://towardsdatascience.com/using-monte-carlo-tree-search-for-your-fantasy-football-draft-6509b78a1c20 | Using Monte Carlo Tree Search for your Fantasy Football draft | [
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Using NLP and deep learning to uncover
Yusuf Aktan
https://towardsdatascience.com/using-nlp-and-deep-learning-to-predict-the-stock-market-64eb9229e102 | Using NLP and Deep Learning to Predict the Stock Market | [
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By observing sonar or radar screens, humans can easily detect tracks, formed by objects that typically are far away and are observed only as points. The respective point patterns can
J ri Sildam
https://towardsdatascience.com/using-recurrent-neural-networks-for-track-detection-in-noise-5e6395c8afae | Using Recurrent Neural Networks for Track Detection In Noise | [
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Most of the work I have done so far has been with neural networks. However, these have a
Gabriel Tseng
https://towardsdatascience.com/using-scikit-learn-to-find-bullies-c47a1045d92f | Using scikit-learn to find bullies | [
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This is a joint post with Yoel Zeldes. It was originally posted in taboola engineering
Inbar Naor
https://towardsdatascience.com/using-uncertainty-to-interpret-your-model-c7b8c9a63072 | Using Uncertainty to Interpret your Model | [
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How we use neural networks to transform billions of streams
Ramzi Karam
https://towardsdatascience.com/using-word2vec-for-music-recommendations-bb9649ac2484 | Using Word2vec for Music Recommendations | [
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Michail Alifierakis is an aspiring data scientist and a Chemical Engineering PhD
Michail Alifierakis
https://towardsdatascience.com/using-yelp-data-to-predict-restaurant-closure-8aafa4f72ad6 | Using Yelp Data to Predict Restaurant Closure | [
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My search for the ultimate
Keith McNulty
https://towardsdatascience.com/utilizing-quosures-to-create-ultra-flexible-filtering-controls-in-r-shiny-f3e5dc461399 | Utilizing quosures to create ultra flexible filtering controls in R Shiny | [
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This blog has a dual purpose. The first is to give a general idea
Javier Gonzalez-Compte
https://towardsdatascience.com/vaccines-and-data-science-a-future-503d00716e4e | Vaccines and Data Science a Future? | [
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In application to binary image denoising
Vadim Smolyakov
https://towardsdatascience.com/variational-inference-ising-model-6820d3d13f6a | Variational Inference: Ising Model | [
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The Road to becoming a self driving car engineer: Part 1
TD
https://towardsdatascience.com/velocious-vehicles-and-how-to-find-them-6e4a8b45f770 | Velocious Vehicles and How to Track Them | [
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Jupyter Notebook Best Practices for Data Science by Jonathan Whitmore has been incredibly helpful and Ive been strongly encouraging team members to adopt at least a subset of them, specifically the post-save hook and the notebook naming convention.
Ceshine Lee
https://towardsdatascience.com/version-control-for-jupyter-... | Version Control for Jupyter Notebook | [
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Often one needs to quickly
Tirthajyoti Sarkar
https://towardsdatascience.com/very-simple-python-script-for-extracting-most-common-words-from-a-story-1e3570d0b9d0 | Very simple Python script for extracting most common words from a story | [
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A month back, I stumbled across a brilliant project by @Nicky Case called The Wisdom and
Ashris
https://towardsdatascience.com/visualising-my-facebook-network-clusters-346bac842a63 | Visualising My Facebook Network Clusters | [
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How we used t-SNE to gain a birds eye view of our customer's
Paul Gradie
https://towardsdatascience.com/visualising-topic-groups-using-t-sne-d44cbcd57ca | Visualizing topic groups using t-SNE | [
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Study and analysis of the data is the very first step of any data science work
Sambit Mahapatra
https://towardsdatascience.com/visualize-world-trends-using-seaborn-in-python-2e563e7d35da | Visualize World Trends using Seaborn in Python | [
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Data is messy. Its often unbalanced, mislabeled, and sprinkled with
Yufeng G
https://towardsdatascience.com/visualize-your-data-with-facets-d11b085409bc | Visualize your data with Facets | [
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Dashboard
Tal Peretz
https://towardsdatascience.com/visualize-your-data-with-google-data-studio-609c38247905 | Visualize Your Data with Google Data Studio | [
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Data visualization to further your enjoyment of narrative
Elijah Meeks
https://towardsdatascience.com/visualizing-archer-bcb80e319625 | Visualizing Archer | [
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How to quickly create a powerful exploratory data analysis visualization
William Koehrsen
https://towardsdatascience.com/visualizing-data-with-pair-plots-in-python-f228cf529166 | Visualizing Data with Pairs Plots in Python | [
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Using World Development Indicators, I visualized energy mix (renewable, nonrenewable
Hannah Yan Han
https://towardsdatascience.com/visualizing-energy-mix-around-the-world-fd457f462c84 | Visualizing energy mix around the world | [
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Perhaps one of the greatest disparities between those who live in the world of data
Thomas Plapinger
https://towardsdatascience.com/visualizing-your-exploratory-data-analysis-d2d6c2e3b30e | Visualizing your Exploratory Data Analysis | [
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In this episode of Cloud AI Adventures, find out how to use TensorBoard to visualize your
Yufeng G
https://towardsdatascience.com/visualizing-your-model-using-tensorboard-796ebb73e98d | Visualizing your model using TensorBoard | [
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Earlier this month, Susie Lu and I released Viz Palette, a tool to help data visualization designers evaluate and improve their palettes. It shows the palette in use across a variety of data visualization types but also measures the individual colors using
Elijah Meeks
https://towardsdatascience.com/viz-palette-for-dat... | Viz Palette for Data Visualization Color | [
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There may be a way to solve the way we vote in the US with some clever use of
Aaron Edell
https://towardsdatascience.com/voting-in-the-us-solved-with-machine-learning-9f2f8ec4b290 | Voting in the US solved with machine learning | [
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While learning different AI methods, I was very interested to see how these methods work. And
Egor Dezhic
https://towardsdatascience.com/watching-modern-ai-methods-in-action-929e106d6a7c | Watching Modern AI Methods in Action | [
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While working on a Data Science project, what is it, that you look for? What is the most
Natasha Sharma
https://towardsdatascience.com/ways-to-detect-and-remove-the-outliers-404d16608dba | Ways to Detect and Remove the Outliers | [
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Ive read a bunch of insightful blogs recently, lots with some sort of focus on data. Blogs like this one, and this one, and lots of others. Data is a hot topic of conversation at the moment, and thats good.
Ellie Craven
https://towardsdatascience.com/we-need-to-talk-about-data-a2d29820203b | We need to talk about data | [
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Last time we converted audio buffers into images. This time well take these images and train a
Boris Smus
https://towardsdatascience.com/web-based-voice-command-recognition-58a9bb1ec8db | Web based voice command recognition | [
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A Small Real-World
William Koehrsen
https://towardsdatascience.com/web-scraping-regular-expressions-and-data-visualization-doing-it-all-in-python-37a1aade7924 | Web Scraping, Regular Expressions, and Data Visualization: Doing it all in Python | [
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For any business to be successful, it needs data. Data/information required can vary with market performance to the competitors data. Web scraping allows the business to get this data from various sources, working on and to be the best in the market. This blog post will
Seema Singh
https://towardsdatascience.com/web-sc... | Web Scraping with BeautifulSoup | [
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Hello everyone! Im starting a new series where I will talk about and test some libraries, code or blogs talking about Python and R and their
Favio V zquez
https://towardsdatascience.com/weekly-python-digest-for-data-science-1st-week-july-83bbf0355c36 | Weekly Python Digest for Data Science (1st Week July) | [
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Hello everyone! In this new seriesI will talk about and test some libraries, code or blogs talking about R and their application to Machine Learning, Deep
Favio V zquez
https://towardsdatascience.com/weekly-r-digest-for-data-science-1st-week-july-df8ce2f3bb72 | Weekly R Digest for Data Science (1st Week July) | [
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Something is missing from your current marketing strategy.
Veda Konduru
https://towardsdatascience.com/what-ai-means-for-marketing-372e7681a08b | What AI means for Marketing! | [
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On the second day of the worlds largest tech conference, attendees gather at the Center Stage to see one of the largest tech corporates showcasing its newest innovations. Its spectaculardrones
St phanie Visser
https://towardsdatascience.com/what-ai-mostly-needs-is-expectation-management-625c90ea147f | What AI mostly needs is expectation management | [
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Adversarial exampleis when you change several pixels in the image of the dog and classifier recognizes a modified image as a shovel.
Dmytro Mishkin
https://towardsdatascience.com/what-are-adversarial-examples-do-they-exist-for-humans-9572e3910219 | What are adversarial examples? Do they exist for humans? | [
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The growing pains of teams and some practical
Ganes Kesari
https://towardsdatascience.com/what-are-the-3-stages-where-data-science-teams-fail-e9f8bcd86825 | What are the 3 Stages where Data Science Teams Fail? | [
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Today I explored TED talks data, their topics and viewerships.
Hannah Yan Han
https://towardsdatascience.com/what-are-the-recurring-topics-in-ted-8392cf9f3fb | What are the recurring topics in TED | [
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Using Python and NYC Open Data
Sarah Schoengold
https://towardsdatascience.com/what-can-311-noise-complaints-in-gowanus-tell-us-about-gentrification-444c7da0a07a | What can 311 noise complaints in Gowanus tell us about gentrification? | [
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Transparency, Trust + Symbiosis
Brian Romer
https://towardsdatascience.com/what-design-brings-to-ai-b44bb3be181e | What design brings to AI | [
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The troubled gaze of an artificial intelligence
Kirsten Menger-Anderson
https://towardsdatascience.com/what-does-it-see-f2dcd9dff9af | What Does It See? | [
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Ill use whatever tools I need to get results. But I wont take a tool on faith.
Schaun Wheeler
https://towardsdatascience.com/what-does-social-science-have-to-offer-the-data-industry-b026211a61ca | What does social science have to offer the data industry? | [
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The numbers dont lie: Democrats are failing to brand the GOP as The Trump Party
Parker Sewell
https://towardsdatascience.com/what-donald-trump-can-learn-from-data-science-eab2ca2ab114 | What Data Science Reveals About President Trump and the GOP | [
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This little post is about what I have learned from my 7 month ML journey. Hope a newbie
Prashant Kikani
https://towardsdatascience.com/what-i-learned-from-7-month-ml-journey-955b0c0ca66b | What I learned from 7 month ML journey | [
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A basic introduction for people new to
Chi-Feng Wang
https://towardsdatascience.com/what-is-a-neural-network-6010edabde2b | A Newbie's Introduction to Convolutional Neural Networks | [
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A Historical Look at What AI Is
Rob Guinness
https://towardsdatascience.com/what-is-artificial-intelligence-part-1-75a6de110141 | What is Artificial Intelligence? Part 1 | [
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The Genius of Alan Turing
Rob Guinness
https://towardsdatascience.com/what-is-artificial-intelligence-part-2-bad0cb97e330 | What is Artificial Intelligence? Part 2 | [
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Bayes rule
Devin Soni
https://towardsdatascience.com/what-is-bayes-rule-bb6598d8a2fd | What is Bayes Rule? | [
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A brief introduction to the statistical learning principle that is the backbone behind most deep neural models.
Brendan Whitaker
https://towardsdatascience.com/what-is-empirical-risk-minimization-erm-ef9edc76b48 | What is empirical risk minimization (ERM)? | [
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An intuitive explanation of expected value with simple examples using games
Devin Soni
https://towardsdatascience.com/what-is-expected-value-4815bdbd84de | What is Expected Value? | [
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The world is filled with data. Lots and lots of data. Everything from pictures, music, words, spreadsheets, videos
Yufeng G
https://towardsdatascience.com/what-is-machine-learning-8c6871016736 | What is Machine Learning? | [
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Robotic Process Automation (RPA)
NewGenApps
https://towardsdatascience.com/what-is-robotic-process-automation-c2a364298248 | What is Robotic Process Automation? | [
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Transfer learning
Pranoy Radhakrishnan
https://towardsdatascience.com/what-is-transfer-learning-8b1a0fa42b4 | What is Transfer Learning? | [
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As the next generation of eager youth look to make their first major career choice
Sean McClure
https://towardsdatascience.com/what-it-means-to-do-math-in-data-science-843f454fddf6 | What it Means to Do Math in Data Science | [
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This year in Lithuania there are plenty of discussions going on how there is a need to introduce
Tadasubonis
https://towardsdatascience.com/what-makes-a-country-prosperous-7cc213974bac | What makes a country prosperous? | [
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So here I am , after one year since my last post. Various things have happened but one thing
Shreyas Raghavan
https://towardsdatascience.com/what-plot-why-this-plot-and-why-not-9508a0cb35ea | What plot ? Why this plot and why not! | [
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The Fundamentals of Neural Networks
SAGAR SHARMA
https://towardsdatascience.com/what-the-hell-is-perceptron-626217814f53 | What the Hell is Perceptron? | [
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Auto ML services provides machine learning at the click of a button, or, at the very
Siobh n K Cronin
https://towardsdatascience.com/whats-auto-ml-b457d2710f9d | What's auto ML? | [
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Naive Bayes (NB) is naive because it makes the assumption that features of a measurement are
Chris Dinant
https://towardsdatascience.com/whats-so-naive-about-naive-bayes-58166a6a9eba | Whats so naive about naive Bayes? | [
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Image Classification using Keras
Prakhar Mishra
https://towardsdatascience.com/whats-that-image-fb6ab703c4a5 | Whats that Image ? | [
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Many of you have likely experienced the same situation that I have encountered where you
Blake Lawrence
https://towardsdatascience.com/whats-the-point-visual-data-reporting-e05c0f4f4479 | Whats the point? Visual Data Reporting | [
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Roles in analytics and picking
Ganes Kesari
https://towardsdatascience.com/whats-the-secret-sauce-to-transforming-into-a-unicorn-in-data-science-94082b01c39d | Whats the secret sauce to transforming into a Unicorn in Data Science? | [
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Validation is probably in the top 5 of most important techniques in data science. I use cross validation as my default validation scheme, but this week I encountered an issue with my validation performance. It took me a while to solveso I would like to share it with you.
Martin Schmitz, PhD
https://towardsdatascience.c... | When Cross Validation Fails | [
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The Inference and Machine Learning Group is Radicles internal data science organization. We work at the intersection of computational statistics, machine learning, and venture capital
Sebastian Quintero
https://towardsdatascience.com/when-do-unicorns-grow-their-horns-series-d-on-average-e75b52ac9dc0 | 2017 in Review | [
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When learning a new programming language, theres always a sense that there will be a few commands, tricks and work-arounds that well keep reusing; commonly known as the 80/20 rule20% of activities are responsible for 80% of the work. And Python naturally lends itself to this paradigm
Rush Kirubi
https://towardsdatascie... | Beginner Python Hacks | [
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I tried to predict the
Tirthajyoti Sarkar
https://towardsdatascience.com/when-machine-learning-tries-to-predict-the-performance-of-machine-learning-6cc6a11bb9bf | When Machine Learning tries to predict the performance of Machine Learning | [
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How to deal with uncertainty and ship impactful work
Conor Dewey
https://towardsdatascience.com/when-your-job-is-done-as-a-data-scientist-c5d887bb0d0e | When Your Job Is Done as a Data Scientist | [
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Artificial intelligence (AI) and machine learning (ML) are at the forefront of the
Karl Utermohlen
https://towardsdatascience.com/where-ai-and-ml-in-marketing-is-headed-6b651f5f7eaa | Where AI and ML in Marketing Is Headed | [
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The world of open data is a strangely complex one, as any data scientist will likely testify. Its a
Adam Pritchard
https://towardsdatascience.com/where-does-our-fish-come-from-9457c90d4ff0 | Where Does Our Fish Come From? | [
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or: Toward a Machine Learning Deployment Environment.
Pascal Potvin
https://towardsdatascience.com/where-the-f-k-do-i-execute-my-model-2591d302bcb1 | Where the F**k do I execute my model? | [
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As an avid book reader I have a problem on how stores like Amazon recommend me books that are related to the one Im about to buy, be it in the form of Customers who bought this item also bought or Sponsored products related to this item. I
Alvaro Videla
https://towardsdatascience.com/wheres-my-depth-first-search-machin... | Wheres my Depth First Search Machine Learning? | [
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We are in the midst of a gold rush in AI. But who will reap the economic benefits? The
Simon Greenman
https://towardsdatascience.com/who-is-going-to-make-money-in-ai-part-i-77a2f30b8cef | Who Is Going To Make Money In AI? Part I | [
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How I built a Twitter bot to predict if
Greg Rafferty
https://towardsdatascience.com/whos-tweeting-from-the-oval-office-building-a-twitter-bot-9c602edf91dd | Whos Tweeting from the Oval Office? Building a Twitter bot | [
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Recently, Alphabet (Googles parent company) has been developing an AI based solution to detect hate speech. This solution (known as Perspective) is being marketed as a way to combat online trolling and vitriol in communities, and has been opened up
cheatmaster30
https://towardsdatascience.com/why-alphabets-ai-cannot-fi... | Why Alphabets AI Cannot Identify Hate Speech | [
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A.I.
Daniel Shapiro, PhD
https://towardsdatascience.com/why-bother-to-bootstrap-your-ai-startup-d94fd62de009 | Why Bother to Bootstrap Your AI Startup? | [
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I just returned from a fantastic week in Stockholm attending International Conference on
Sara Hooker
https://towardsdatascience.com/why-data-for-good-lacks-precision-87fb48e341f1 | Why data for good lacks precision. | [
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Invest Minutes to Possibly Save Your Company Millions
Eric Luellen
https://towardsdatascience.com/why-data-science-succeeds-or-fails-c24edd2d2f9 | Why Data Science Succeeds or Fails: | [
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Three main reasons why Gaussian distribution is so popular with
Abhishek Parbhakar
https://towardsdatascience.com/why-data-scientists-love-gaussian-6e7a7b726859 | Why Data Scientists love Gaussian? | [
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1986 was a great year. In the heyday of the worst-dressed decade in history, the
Hugh Harvey
https://towardsdatascience.com/why-deep-learning-may-be-best-for-breast-7725d1440fde | Why deep learning may be best for breast | [
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If you should believe the media, Deepfakes equals the end of days. Fake news, fake evidence, this
Sven Charleer
https://towardsdatascience.com/why-deepfakes-are-a-good-thing-10ceb86deaed | Why Deepfakes are a good thing | [
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Remember that the
Alex P. Miller
https://towardsdatascience.com/why-do-we-care-so-much-about-explainable-algorithms-in-defense-of-the-black-box-d9e3bc01e0dc | Why do we care so much about explainable algorithms? In defense of the black box | [
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The deadline was nearing. I had written about 30 pages, and had to at least write 30 more to complete
Imaad Mohamed Khan
https://towardsdatascience.com/why-everyone-is-a-data-scientist-b91abd34ad44 | Why everyone is a Data Scientist | [
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Eating a bowl of noodles has never been easy for me. Now I dont blame the chopsticks (yet to learn how to use em) but my aversion towards the cabbage in the noodles. Sorting through those yummy strands, I neatly pick out the shreds of cabbage before
Ida Jessie Sagina
https://towardsdatascience.com/why-go-large-with-dat... | Why go large with Data for Deep Learning? | [
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0.022674262523651123,
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-0.057210545... |
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