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After five years of working in the game industry as an analyst and data scientist (DS), I
Ben Weber
https://towardsdatascience.com/from-games-to-fintech-my-ds-journey-b7169f08b6ad | From Games to FinTech: My DS Journey | [
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A 50 Year Look At Human And Computer Vision
SeattleDataGuy
https://towardsdatascience.com/from-neuroscience-to-computer-vision-e86a4dea3574 | From Neuroscience To Computer Vision | [
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2011 ACM RecSys
Vivian Zheng
https://towardsdatascience.com/frontiers-of-recommendation-systems-diversity-f668adad502c | Frontiers of Recommendation Systems & Diversity | [
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Im frustrated by the scope of tools currently available for data visualization work. Theyre rapidly
Jasper McChesney
https://towardsdatascience.com/frustrations-with-dataviz-tools-de27cbcd2ff1 | Frustrations with DataViz Tools | [
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This is part 2 of a 2 part series on the basic full stack web development tools Data Scientists would need to build basic interactive visualizations on the
Seth Weidman
https://towardsdatascience.com/full-stack-basics-for-data-scientists-and-other-non-web-developers-part-2-jquery-d3-ajax-and-90f629c6b952 | Full Stack Basics for Data Scientists and Other Non-Web Developers, Part 2: jQuery, D3, AJAX and Flask | [
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Baseball or Cricket? US $ or Canadian $?
Nikhil Balaji
https://towardsdatascience.com/fun-with-small-image-data-sets-8c83d95d0159 | Fun with small image data-sets | [
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Is the human wearing glasses?
Nikhil Balaji
https://towardsdatascience.com/fun-with-small-image-data-sets-part-2-54d683ca8c96 | Fun with small image data-sets (Part 2) | [
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Replication without repetition!
Thomas Mock
https://towardsdatascience.com/functional-programming-in-r-with-purrr-469e597d0229 | Functional Programming in R with purrr | [
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Data science is a broad term and includes job roles with many different functions within organizations. This post
Ben Weber
https://towardsdatascience.com/functions-of-data-science-4afd5341a659 | Functions of Data Science | [
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NYU Skirball Center, October 31st 2017
David Fisher
https://towardsdatascience.com/future-labs-ai-summit-cliff-notes-8ac185cef212 | Future Labs AI Summit Cliff Notes | [
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Graphing the Big Picture
Joel Baum
https://towardsdatascience.com/game-of-thrones-season-7-5-episode-1-27bdc906e6df | Game of ThronesSeason 7.5Episode 1 | [
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Its a Small World of Ice and Fire
Joel Baum
https://towardsdatascience.com/game-of-thrones-season-7-5-episode-2-dd518f6b03c | Game of ThronesSeason 7.5Episode 2 | [
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Character Network Positions and Advantages
Joel Baum
https://towardsdatascience.com/game-of-thrones-season-7-5-episode-3-fcf1f35af7c0 | Game of ThronesSeason 7.5Episode 3 | [
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Who Will Survive Season 8? Network Positions that Kill
Joel Baum
https://towardsdatascience.com/game-of-thrones-season-7-5-episode-4-abb12ee1e43d | Game of ThronesSeason 7.5Episode 4 | [
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Can we learn something from the word vector representations
JC Testud
https://towardsdatascience.com/game-of-thrones-word-embeddings-does-r-l-j-part-2-30290b1c0b4b | Game of Thrones Word Embeddings, does R+L = J ?part 2 | [
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This article will be a bit different from previous ones which are based on some new technologies to use in your projects.
NerdzLab
https://towardsdatascience.com/game-theory-minimax-f84ee6e4ae6e | Game theoryMinimax | [
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GAN models can suffer badly in the following areas comparing to other deep networks.
Jonathan Hui
https://towardsdatascience.com/gan-ways-to-improve-gan-performance-acf37f9f59b | GANWays to improve GAN performance | [
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Learn how Neural Network training can be
Suryansh S.
https://towardsdatascience.com/gas-and-nns-6a41f1e8146d | Genetic Algorithms + Neural Networks = Best of Both Worlds | [
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Deep learning has proven its superiority in many domains, in a variety of tasks
Yoel Zeldes
https://towardsdatascience.com/gated-multimodal-units-for-information-fusion-966a9a2e1c54 | Gated Multimodal Units for Information Fusion | [
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Depth is a critical part of modern neural networks. They enable efficient representations through
Hadayat Seddiqi
https://towardsdatascience.com/gating-and-depth-in-neural-networks-b2c66ae74c45 | Gating and Depth in Neural Networks | [
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It has been long time since I wrote the first machine learning for everyone article. From now on, I will try to
Semih Akbayrak
https://towardsdatascience.com/generalized-linear-models-8738ae0fb97d | Generalized Linear Models | [
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Simulating usage behavior
Jan Osolnik
https://towardsdatascience.com/generating-product-usage-data-from-scratch-with-pandas-319487590c6d | Generating product usage data from scratch with Pandas | [
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In Part I of this series, the original GAN paper was presented. Although being clever
Zak Jost
https://towardsdatascience.com/generative-adversarial-networks-part-ii-6212f7755c1f | Generative Adversarial NetworksPart II | [
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Ill jump straight into what we have explained on a high-level last time. The code is also available on GitHub and on Medium. This part is identical to the Jupyter notebook, except it is
Jakub Langr
https://towardsdatascience.com/generative-adverserial-networks-semi-supervised-learning-24f5fb027934 | GENERATIVE ADVERSERIAL NETWORKS & SEMI-SUPERVISED LEARNING | [
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This tutorial will implement the genetic algorithm optimization technique in Python based on a simple example in which we are trying to maximize the output of an equation. The tutorial uses the decimal representation for genes, one point crossover, and
Ahmed Gad
https://towardsdatascience.com/genetic-algorithm-implemen... | Genetic Algorithm Implementation in Python | [
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GEN Summit
Paul Bradshaw
https://towardsdatascience.com/gensummit-2018-ais-breakthrough-year-in-publishing-6fa5a78154be | #GENSummit 2018: AIs breakthrough year in publishing | [
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Scikit-learn has long been a popular library for getting started with machine learning
Yufeng G
https://towardsdatascience.com/get-going-with-scikit-learn-on-kaggle-32045d238eee | Get going with Scikit-Learn on Kaggle | [
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The rise of fake Everything
Sarvasv Kulpati
https://towardsdatascience.com/get-ready-to-never-trust-anything-on-the-internet-ever-again-8978352fa91b | Get Ready To Never Trust Anything On The Internet Ever Again | [
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Hands up if this strikes a chord with any data people out there. Your boss gives you a
Blair
https://towardsdatascience.com/get-stuck-in-with-contributing-to-pandas-fea87d2ac99 | Get Stuck in with Contributing to pandas | [
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In this post, I am going to discuss Apache Kafka and how Python programmers can use
Adnan Siddiqi
https://towardsdatascience.com/getting-started-with-apache-kafka-in-python-604b3250aa05 | Getting started with Apache Kafka in Python | [
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One of the top things that I get asked about when I give talks is Google Cloud AutoML
Yufeng G
https://towardsdatascience.com/getting-started-with-automl-vision-alpha-ba769121235c | Getting started with AutoML Vision alpha | [
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Introduction
Percy Jaiswal
https://towardsdatascience.com/getting-started-with-reinforcement-q-learning-77499b1766b6 | Getting Started with Reinforcement Q Learning | [
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A two-dimensional example of Jacobian-based adversarial attacks and
Adrian Botta
https://towardsdatascience.com/getting-to-know-a-black-box-model-374e180589ce | Getting to know a black-box model: | [
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All about serverless what, why and how?
Anuradha Wickramarachchi
https://towardsdatascience.com/go-serverless-with-firebase-5348dedb70e9 | Go Serverless with Firebase | [
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Seeing beyond what my eyes are seeing is something I apply to every aspect in my life. In this article Ill show how Agile Data Science Workflows is helping
Favio V zquez
https://towardsdatascience.com/going-beyond-with-agile-data-science-fcff5aaa9f0c | Going Beyond with Agile Data Science Workflows | [
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With recent advancements in deep learning based computer vision models, object detection applications
Lars Hulstaert
https://towardsdatascience.com/going-deep-into-object-detection-bed442d92b34 | Going deep into object detection | [
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Neural networks suffer from a few pernicious problems. Chief among them is overfittinggiven enough training-time, a neural network will exactly predict the training data, while losing the ability to comprehend new data. It completely fails to generalize what it
Anthony Repetto
https://towardsdatascience.com/going-sidew... | Going Sideways in Neural Networks | [
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Just a few days ago Google AI launched an object detection competition on Kaggle
George Seif
https://towardsdatascience.com/google-ais-new-object-detection-competition-6dde25cf099d | Google AIs New Object Detection Competition | [
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An Overview
Sebastian Kwiatkowski
https://towardsdatascience.com/gpu-accelerated-neural-networks-in-javascript-195d6f8e69ef | GPU-accelerated Neural Networks in JavaScript | [
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Optimization
Imad Dabbura
https://towardsdatascience.com/gradient-descent-algorithm-and-its-variants-10f652806a3 | Gradient Descent Algorithm and Its Variants | [
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An analogy for fun
Danilo Pena
https://towardsdatascience.com/gradient-descent-and-cryptocurrency-995693ddae6b | Gradient Descent and Cryptocurrency | [
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I am often asked these two questions and that is Can you please explain gradient descent? and
Koo Ping Shung
https://towardsdatascience.com/gradient-descent-simply-explained-1d2baa65c757 | Gradient Descent: Simply Explained? | [
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In March 2017, OpenAI released a blog post on evolution strategies, an optimisation technique
Lars Hulstaert
https://towardsdatascience.com/gradient-descent-vs-neuroevolution-f907dace010f | Gradient descent vs. neuroevolution | [
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Traditional statistical methods in the Neo4j graph database
Lauren Shin
https://towardsdatascience.com/graphs-and-linear-regression-734d1446e9cd | Graphs and ML: Linear Regression | [
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Same neo4j linear regression procedures, now unlimited
Lauren Shin
https://towardsdatascience.com/graphs-and-ml-multiple-linear-regression-c6920a1f2e70 | Graphs and ML: Multiple Linear Regression | [
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Lets dive into the interplay
Danilo Pena
https://towardsdatascience.com/ground-truth-versus-bias-99f68e5e16b | Ground Truth Versus Bias | [
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Learn to tackle this laborious process with a systematic approach!
Kyle M Shannon
https://towardsdatascience.com/guide-to-reading-academic-research-papers-c69c21619de6 | Guide to Reading Academic Research Papers | [
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How giving up our right to private data hurts us all.
jacob zelko
https://towardsdatascience.com/has-data-become-the-new-golden-calf-8a199e386642 | Has Data Become the New Golden Calf | [
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Im a student at General Assemblys Data Science Immersive course, which is awesome. In the ten weeks Ive
Chaim Gluck
https://towardsdatascience.com/has-your-data-been-corrupted-24e6c5677163 | Has Your Data Been Corrupted? | [
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This article show Deep Convolutional Generative Adversarial Networksa.k.a DCGAN
Naoki Shibuya
https://towardsdatascience.com/having-fun-with-deep-convolutional-gans-f4f8393686ed | Having Fun with Deep Convolutional GANs | [
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The UI design was not wrong !!
Venkat Raman
https://towardsdatascience.com/hawaii-false-missile-alert-removing-confusion-from-confusion-matrix-75b53f8caab9 | Hawaii False Missile AlertRemoving Confusion From Confusion Matrix | [
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TensorFlow is an open-source software library developed by Google which is used for machine learning. It is
Sidath Asiri
https://towardsdatascience.com/hello-world-in-tensorflow-973e6c38e8ed | Hello World in TensorFlow | [
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The growth of enterprise data and the impacts on IT is well documented. As the business requests for insights have
Nate Vaziri
https://towardsdatascience.com/herding-the-wranglers-1c21f2ea499 | Herding the wranglers | [
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In 2006, marketing commentator Michael Palmer had blogged
Deena Zaidi
https://towardsdatascience.com/here-is-how-big-data-is-changing-the-oil-industry-13c752e58a5a | Role of Data Analytics in the Oil Industry | [
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The amount of change expected in the next few years is daunting, relentless and coming
Manish Bahl
https://towardsdatascience.com/heroes-the-future-of-it-infrastructure-a426b69090a7 | [
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We also know that the discipline of computer vision proposes more and more support into
Nicolas Bortolotti
https://towardsdatascience.com/hey-google-where-is-my-pet-tensorflow-object-detection-contribution-9c1d1fdd0443 | Hey Google, where is my pet? TensorFlow object detection contribution | [
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Hello world! As we have just launched our product beta, we
The Data Science Interview
https://towardsdatascience.com/hi-we-are-the-data-science-interview-e34e39d56340 | Hi, we are The Data Science Interview! | [
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Geoffrey Hinton is onto something. His model of machine intelligence, which relies upon neuron-clumps that he calls capsules, is the best
Anthony Repetto
https://towardsdatascience.com/hinton-1e6d26a64bd6 | Hinton++ | [
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Visualizing One-Dimensional Data in Python
William Koehrsen
https://towardsdatascience.com/histograms-and-density-plots-in-python-f6bda88f5ac0 | Histograms and Density Plots in Python | [
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I try my best to read ML and AI related papers on a regular basis. Its the
Paul-Louis Pr ve
https://towardsdatascience.com/history-of-convolutional-blocks-in-simple-code-96a7ddceac0c | History of Convolutional Blocks in simple Code | [
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If you are reading this article, you are already surrounded by AI-powered tech more than you can imagine. From
Abhishek Parbhakar
https://towardsdatascience.com/hot-topics-in-ai-research-4367bdd93564 | Hot topics in AI research | [
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Artificial Intelligence is being largely discussed nowadays by its potential to automate tasks that required repetitive
Priscilla Ara jo
https://towardsdatascience.com/how-ai-is-changing-pr-14b40b8cd619 | How AI is Changing PR | [
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The huge technological progress of the last decade addressed and greatly impacted the
Nicolas Fekos
https://towardsdatascience.com/how-an-ai-engine-can-improve-your-business-f8dc91e8371 | How an AI Engine can improve your business | [
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Big data has been all over the news ever since
PromptCloud
https://towardsdatascience.com/how-big-data-can-impact-creativity-in-the-near-future-95e0a626840a | How Big Data Can Impact Creativity in the Near Future | [
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An experimental study on how size of the data affects your machine
Monik Raj
https://towardsdatascience.com/how-big-should-be-your-data-fdace6e627e4 | How Big should be your Data? | [
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How decentralization and token economies can
Devin Soni
https://towardsdatascience.com/how-blockchain-will-revolutionize-data-science-part-1-39cea8dc6713 | How Blockchain Will Revolutionize Data Science (Part 1) | [
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How blockchain technology will empower the user with control of
Shaan Ray
https://towardsdatascience.com/how-blockchains-will-enable-privacy-1522a846bf65 | How Blockchains Will Enable Privacy | [
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Im pretty transparent about the fact that my writing on medium gets me interesting connections that can turn into leads in my business development pipeline. The analytics for the 35 articles I have published on medium.com tell me that youmy readerslike to
Daniel Shapiro, PhD
https://towardsdatascience.com/how-can-i-wri... | How Can I Write Better Articles on AI? | [
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How deep a Machine Learning model needs to be for
Thimira Amaratunga
https://towardsdatascience.com/how-deep-should-it-be-to-be-called-deep-learning-a7b1a6ab5610 | How deep should it be to be called Deep Learning? | [
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Understanding a scenario where your machine learning model can fail
Shikhar Gupta
https://towardsdatascience.com/how-dis-similar-are-my-train-and-test-data-56af3923de9b | How (dis)similar are my train and test data? | [
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Guest written by Rebecca Njeri!
SeattleDataGuy
https://towardsdatascience.com/how-do-machine-learning-algorithms-learn-bias-555809a1decb | How Do Machine Learning Algorithms Learn Bias? | [
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Using the data behind TED Talks to explore speech
Kate B umli
https://towardsdatascience.com/how-do-people-talk-about-ideas-worth-spreading-c824216f411e | How Do People Talk About Ideas Worth Spreading? | [
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In our last blog, we learnt about the basics of What a recommendation engine
Maruti Techlabs
https://towardsdatascience.com/how-does-a-recommendation-engine-really-work-656bdf12a5fc | How Does a Recommendation Engine Really Work? | [
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Predictive analytics can be defined as a form of
Clark Boyd
https://towardsdatascience.com/how-five-businesses-are-using-ai-and-big-data-today-784abeb6f9ef | How five businesses are using AI and big data today | [
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And the rest of the bucket of buzzwords
SeattleDataGuy
https://towardsdatascience.com/how-healthcare-could-use-data-science-to-help-reduce-costs-2c1e67bd1611 | Using Data Science To Reduce Healthcare Costs | [
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Reverse engineering iPhone Xs new
Norman Di Palo
https://towardsdatascience.com/how-i-implemented-iphone-xs-faceid-using-deep-learning-in-python-d5dbaa128e1d | How I implemented iPhone Xs FaceID using Deep Learning in Python. | [
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TL;DR
Ernest Kim
https://towardsdatascience.com/how-i-learned-to-love-parallelized-applies-with-python-pandas-dask-and-numba-f06b0b367138 | Data Pre-Processing in Python: How I learned to love parallelized applies with Dask and Numba | [
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Things have changed. Certain types of problems used to be really hard, or require a lot of
Aaron Edell
https://towardsdatascience.com/how-i-use-machine-learning-to-save-time-49f8b0ee0881 | How I use machine learning to save time | [
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Recently I met a few friends in preparation for a machine learning panel on
SeattleDataGuy
https://towardsdatascience.com/how-mens-wearhouse-could-use-data-science-4a194f8fdbb | How Mens Wearhouse Could Use Data Science | [
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Using data science to uncover how concert tickets are
Yusuf Aktan
https://towardsdatascience.com/how-much-is-your-concert-ticket-really-worth-382a8d38333 | How Much is Your Concert Ticket Really Worth? | [
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Like when writing that test that you studied for so long. You hope youre going to
Capturly
https://towardsdatascience.com/how-much-is-your-web-analytics-data-worth-cb820a1c45a5 | How Much is Your Web Analytics Data Worth? | [
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In my other posts, I have covered topics such as: How to combine machine learning and physics based modeling, and how machine learning can be used for production optimization. But in
Vegard F
https://towardsdatascience.com/how-not-to-use-machine-learning-for-time-series-forecasting-avoiding-the-pitfalls-19f9d7adf424 | How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls | [
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Age Assessment using 3D Knee MRIs and Convolutional Neural Networks
Paul-Louis Pr ve
https://towardsdatascience.com/how-old-am-i-f62538487d36 | How old am I? | [
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Of the many challenges facing developers of artificial intelligence in medicine, it is access
Hugh Harvey
https://towardsdatascience.com/how-open-health-data-can-save-the-nhs-a2f7059af0f7 | How open health data can save the NHS | [
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In this article, we showed
Tirthajyoti Sarkar
https://towardsdatascience.com/how-the-good-old-sorting-algorithm-helps-a-great-machine-learning-technique-9e744020254b | How the good old sorting algorithm helps a great machine learning technique | [
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This is part of an ongoing series on interviewing for data science roles. You can check out the first part, covering SQL, here and the second, covering statistics, here.
Carson Forter
https://towardsdatascience.com/how-to-ace-data-science-interviews-r-python-3a49982000de | How To Ace Data Science Interviews: R & Python | [
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This is part of an ongoing series on interviewing for data science roles. You can check
Carson Forter
https://towardsdatascience.com/how-to-ace-data-science-interviews-sql-b71de212e433 | How To Ace Data Science Interviews: SQL | [
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A few stereotype of peoples not ready to be data scientists and some
Pascal Potvin
https://towardsdatascience.com/how-to-be-a-bad-data-scientist-434dfb5a209c | How to be a bad data scientist! | [
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A couple of weeks ago, I wrote and published my second Kaggle kernel. I was intrigued by their State of
Jack Cook
https://towardsdatascience.com/how-to-become-a-data-scientist-8c0ea546ab81 | How to Become a Data Scientist | [
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I am a recruiter specialised in the field of data science
Experfy
https://towardsdatascience.com/how-to-become-a-data-scientist-part-1-3-8706a62b809e | How to Become a Data Scientist (Part 1/3) | [
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If data science is your goal, I will give you some pointers on how
Pascal Potvin
https://towardsdatascience.com/how-to-become-a-good-data-scientist-d0f86e28060a | How to become a good data scientist | [
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How do you get a job in data science?
Michael Galarnyk
https://towardsdatascience.com/how-to-build-a-data-science-portfolio-5f566517c79c | How to Build a Data Science Portfolio | [
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Lets build a virtual garden!
Avinash Royyuru
https://towardsdatascience.com/how-to-build-a-dynamic-garden-using-machine-learning-d589468f7c04 | How to build a dynamic garden using machine learning | [
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Keras is one of the most popular Deep Learning libraries out there at the moment and
Niklas Donges
https://towardsdatascience.com/how-to-build-a-neural-network-with-keras-e8faa33d0ae4 | How to build a Neural Network with Keras | [
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A Small Educative Project for
Tristan Ganry
https://towardsdatascience.com/how-to-build-animated-charts-like-hans-rosling-doing-it-all-in-r-570efc6ba382 | How to build Animated Charts like Hans Roslingdoing it all in R | [
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You cant just add AI to a project and expect it to work. It isnt magic dust that can be
Chris Butler
https://towardsdatascience.com/how-to-build-trustworthy-ai-products-3f49de63209a | How to build trustworthy AI products | [
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A beginners guide to understanding the
James Loy
https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6 | How to build your own Neural Network from scratch in Python | [
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It is the heyday for Data Science
Kirill Eremenko
https://towardsdatascience.com/how-to-choose-a-data-science-job-53007d7f195f | How to choose a Data Science Job. | [
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Advice for professionals in
Tirthajyoti Sarkar
https://towardsdatascience.com/how-to-choose-effective-moocs-for-machine-learning-and-data-science-8681700ed83f | How to choose effective MOOCs for machine learning and data science? | [
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Deep Learning has become the go-to method for solving many challenging real-world
George Seif
https://towardsdatascience.com/how-to-collect-your-deep-learning-dataset-2e0eefc0ba24 | How to collect your deep learning dataset | [
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-0.36421042680740356,
-0.21825112402439117,
0.16988199949264526,
-0.23811332881450653,
-0.3944240212440491,
0.09060681611299515,
-0.0261021982... |
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