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Better insights through beautiful visualizations
Carolina Bento
https://towardsdatascience.com/customizing-plots-with-python-matplotlib-bcf02691931f | Customizing Plots with Python Matplotlib | [
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9 Steps to Building a
Dave Smith
https://towardsdatascience.com/cutting-edge-face-recognition-is-complicated-these-spreadsheets-make-it-easier-e7864dbf0e1a | Cutting-Edge Face Recognition is Complicated. These Spreadsheets Make it Easier. | [
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Credits
Manish Chablani
https://towardsdatascience.com/cyclegans-and-pix2pix-5e6a5f0159c4 | CycleGANS and Pix2Pix | [
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Effective root cause analysis is the heart of any problem solving method such as Six Sigma, Lean, Root Cause
Juran
https://towardsdatascience.com/daily-root-cause-analysis-6662a1bbc81b | Daily Root Cause Analysis | [
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In our last part we discussed the soft skills analysts needed to be a well rounded
SeattleDataGuy
https://towardsdatascience.com/data-analysis-for-everyone-part-2-cf1c79441940 | Intro To Data Analysis For Everyone, Part 2 | [
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A quick and simple explanation of a very important issue.
Jesse Paquette
https://towardsdatascience.com/data-analysis-has-a-serious-last-mile-problem-83892ea52a65 | Data analysis has a serious Last Mile problem | [
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In this article, we
Tirthajyoti Sarkar
https://towardsdatascience.com/data-analytics-with-python-by-web-scraping-illustration-with-cia-world-factbook-abbdaa687a84 | Data Analytics with Python by Web scraping: Illustration with CIA World Factbook | [
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Experimenting with simple data augmentation parameters to get the best results
Amrit Virdee
https://towardsdatascience.com/data-augmentation-experimentation-3e274504f04b | Data Augmentation Experimentation | [
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Lets talk about tables, trees and graphs
Maxim Zaks
https://towardsdatascience.com/data-comes-in-different-shapes-and-sizes-ac5b411456c4 | Data comes in different shapes and sizes | [
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Wield Data Correlation properly to
Soham Chatterjee
https://towardsdatascience.com/data-correlation-can-make-or-break-your-machine-learning-project-82ee11039cc9 | Data Correlation can make or break your Machine Learning Project | [
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Welcome to my weekly roundup of data-driven things I noticed on the web last week. This is week 22 (last weeks post is here).
Benjamin Cooley
https://towardsdatascience.com/data-curious-02-10-2017-a-roundup-of-data-stories-datasets-and-visualizations-from-last-week-237f117107c0 | Data Curious 02.10.2017: A roundup of data stories, datasets and visualizations from last week | [
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Welcome to my weekly roundup of data-driven things I noticed on the web last week. This is week 16 (last weeks post is here).
Benjamin Cooley
https://towardsdatascience.com/data-curious-07-08-2017-a-roundup-of-data-stories-datasets-and-visualizations-from-last-week-a43b875e1bc3 | Data Curious 07.08.2017: A roundup of data stories, datasets and visualizations from last week | [
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Welcome to my weekly roundup of data-driven things I noticed on the web last week. This is week 17 (last weeks post is here).
Benjamin Cooley
https://towardsdatascience.com/data-curious-14-08-2017-a-roundup-of-data-stories-datasets-and-visualizations-from-last-week-ec998b7d0caf | Data Curious 14.08.2017: A roundup of data stories, datasets and visualizations from last week | [
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Welcome to my weekly roundup of data-driven things I noticed on the web last week. This is week 20 (last weeks post is here).
Benjamin Cooley
https://towardsdatascience.com/data-curious-20-09-2017-a-roundup-of-data-stories-datasets-and-visualizations-from-last-week-5281deb27d13 | Data Curious 20.09.2017: A roundup of data stories, datasets and visualizations from last week | [
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Welcome to my weekly roundup of data-driven things I noticed on the web last week. This is week 21 (last weeks post is here).
Benjamin Cooley
https://towardsdatascience.com/data-curious-25-09-2017-a-roundup-of-data-stories-datasets-and-visualizations-from-last-week-30a40846a787 | Data Curious 25.09.2017: A roundup of data stories, datasets and visualizations from last week | [
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Combined with mystique, confusion, and general misunderstandingthe phenomenon of data being
Peter Binggeser
https://towardsdatascience.com/data-does-not-have-intrinsic-value-2824c2409d86 | Data Does Not Have Intrinsic Value | [
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This is the second article of a series of four and focuses on data-driven culture: the
Pedro Uria-Recio
https://towardsdatascience.com/data-driven-culture-the-reptilian-brain-aa80e3ebd121 | Data-Driven Culture & the Reptilian Brain | [
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If love is blind, why is lingerie so popular? Dorothy Parker
Jekaterina Kokatjuhha
https://towardsdatascience.com/data-driven-lingerie-shopping-6dc61c57f97f | Data-driven lingerie shopping | [
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There is a high demand for data engineers these days. I can see job proposals
Guillaume Payen
https://towardsdatascience.com/data-engineers-are-there-did-you-see-them-9b6452e92b23 | Data engineers are there, can you see them ? | [
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Big data is all around us, but how can it be best used to enhance the veterinary
Rob Harrand
https://towardsdatascience.com/data-in-veterinary-your-untapped-commodity-1d6ac67c3d5e | Veterinary Data: Your Untapped Commodity | [
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Design, ethnography, and future-proof data science
Schaun Wheeler
https://towardsdatascience.com/data-is-a-stakeholder-31bfdb650af0 | Data is a stakeholder | [
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Its been a short week, what with the Bank Holiday, but weve still be pretty busy. Oh, and the
David Ottewell
https://towardsdatascience.com/data-journalism-highlights-this-week-5b603d9d4b92 | Data journalism highlights this week | [
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A detailed examination of
Jason Forrest
https://towardsdatascience.com/data-journalism-in-the-study-of-w-e-b-du-bois-the-negro-problem-part-2-of-4-e5ea9b976adc | Data Journalism in the study of W.E.B. Du Bois' "The Negro Problem" (Part 2) | [
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1. Introduction to data mining and tools
Anuradha Wickramarachchi
https://towardsdatascience.com/data-mining-bc7feca95887 | Data Mining | [
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2. Introduction to Pandas data structures and essential operations
Anuradha Wickramarachchi
https://towardsdatascience.com/data-mining-e06cf1a0b7ee | Data Mining | [
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Data mining is a very popular topic nowadays. Unlike a few years ago, everything is bind with data now and we are capable
Sidath Asiri
https://towardsdatascience.com/data-mining-in-brief-26483437f178 | Data Mining in Brief | [
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This is a blog for people new to Data Science, like me. I hope we learn together through this process
Abhinav Ralhan
https://towardsdatascience.com/data-preparation-and-exploration-5e09b92cf00e | Data Preparation and Exploration | [
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Part OneData Structures, Types and
Melody Ucros
https://towardsdatascience.com/data-preprocessing-for-non-techies-basic-terms-and-definitions-ea517038a4e5 | Data Preprocessing For Non-Techies: Basic Terms and Definitions | [
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Part TwoChecklist of Most
Melody Ucros
https://towardsdatascience.com/data-preprocessing-for-non-techies-feature-exploration-and-engineering-f1081438a5de | Data Preprocessing for Non-Techies: Feature Exploration and Engineering | [
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Minder Suggestion Engine:
Numan Sheikh
https://towardsdatascience.com/data-science-43c246d4eebc | Data Science | [
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Charting the Great Weight Challenge of 2017
William Koehrsen
https://towardsdatascience.com/data-science-a-practical-application-7056ec22d004 | Data Science: A Personal Application | [
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Ah the dreaded machine learning interview. You feel like you know everything until youre tested on it! But it doesnt have to be this way.
George Seif
https://towardsdatascience.com/data-science-and-machine-learning-interview-questions-3f6207cf040b | Data Science and Machine Learning Interview Questions | [
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Presented at Data Science Salon in Dallas by Brian Kursar, Vice President and Chief Data Scientist at
Formulated.by
https://towardsdatascience.com/data-science-at-toyota-connected-69bf50982b09 | Data Science at Toyota Connected | [
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A Practical Way to Create
Andrew Olton
https://towardsdatascience.com/data-science-case-study-optimizing-product-placement-in-retail-part-1-2e8b27e16e8d | Data Science Case Study: Optimizing Product Placement in Retail (Part 1) | [
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Theres a number of compelling reasons for data scientists to write books. I wanted to
Ben Weber
https://towardsdatascience.com/data-science-for-startups-blog-book-bf53f86ca4d5 | Data Science for Startups: Blog -> Book | [
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Part three of my ongoing series about building a data science discipline at a startup
Ben Weber
https://towardsdatascience.com/data-science-for-startups-data-pipelines-786f6746a59a | Data Science for Startups: Data Pipelines | [
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Part ten of my ongoing series about building a data science discipline at a startup, and
Ben Weber
https://towardsdatascience.com/data-science-for-startups-deep-learning-40d4d8af8009 | Data Science for Startups: Deep Learning | [
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I recently changed industries and joined a startup company where Im responsible for
Ben Weber
https://towardsdatascience.com/data-science-for-startups-introduction-80d022a18aec | Data Science for Startups: Introduction | [
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Part seven of my ongoing series about building a data science discipline at a
Ben Weber
https://towardsdatascience.com/data-science-for-startups-model-production-b14a29b2f920 | Data Science for Startups: Model Production | [
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Part two of my data science for startups series focused on Python.
Ben Weber
https://towardsdatascience.com/data-science-for-startups-model-services-2facf2dde81d | Data Science for Startups: Model Services | [
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Part six of my ongoing series about building a data science discipline at a
Ben Weber
https://towardsdatascience.com/data-science-for-startups-predictive-modeling-ec88ba8350e9 | Data Science for Startups: Predictive Modeling | [
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One of the pieces of feedback I received for my blog series Data Science for Startups was
Ben Weber
https://towardsdatascience.com/data-science-for-startups-r-python-2ca2cd149c5c | Data Science for Startups: R -> Python | [
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Part two of my ongoing series about building a data science discipline at a startup. You
Ben Weber
https://towardsdatascience.com/data-science-for-startups-tracking-data-4087b66952a1 | Data Science for Startups: Tracking Data | [
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Through my discussion with many people on data science and artificial intelligence, I often hear people saying
Koo Ping Shung
https://towardsdatascience.com/data-science-in-start-ups-c3cb13286dc4 | Data Science in Start-ups? | [
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Data Science is quite a large and diverse field. As a result, it is really difficult to be a jack of all
Syed Sadat Nazrul
https://towardsdatascience.com/data-science-interview-guide-4ee9f5dc778 | Data Science Interview Guide | [
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Meet the Thread Genius team at
Vishal Kumar
https://towardsdatascience.com/data-science-machine-learning-and-artificial-intelligence-for-art-1ac48c4fad41 | Data Science, Machine Learning and Artificial Intelligence for Art | [
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Moneyballing the ICO investment game
DebajyotiDeb) Ray
https://towardsdatascience.com/data-science-to-evaluate-icos-f5d59948f05a | Data Science to evaluate ICOs | [
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It pays to even vectorize
Tirthajyoti Sarkar
https://towardsdatascience.com/data-science-with-python-turn-your-conditional-loops-to-numpy-vectors-9484ff9c622e | Data science with Python: Turn your conditional loops to Numpy vectors | [
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What is Reproducibility in Data Science and Why Should We Care?
Zach Scott
https://towardsdatascience.com/data-sciences-reproducibility-crisis-b87792d88513 | Data Sciences Reproducibility Crisis | [
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The information age has revolutionized the way we interact, communicate and are
Lucas Kohorst
https://towardsdatascience.com/data-transparency-in-an-un-private-internet-8179805f70e7 | Data Transparency in an Un-Private Internet | [
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Data Types are an important concept of statistics, which needs to be understood, to correctly apply statistical
Niklas Donges
https://towardsdatascience.com/data-types-in-statistics-347e152e8bee | Data Types in Statistics | [
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My effort to liberate data from spreadsheets
William Koehrsen
https://towardsdatascience.com/data-visualization-hackathon-style-c6dcaabbf626 | Data Visualization Hackathon Style | [
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Friday Open Sourcery Training: Volume# 9
Alex Wilson
https://towardsdatascience.com/data-visualization-with-d3-js-dimple-be001bca3499 | Data Visualization with D3.js & Dimple | [
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This blog post initially appeared on
Chiara_AI
https://towardsdatascience.com/dating-apps-bet-machine-learning-will-help-you-find-love-9e9b8fb62f37 | Dating apps bet machine learning will help you find love | [
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Decision trees belongs to the
Prasad Patil
https://towardsdatascience.com/decision-tree-data-scientists-magic-bullet-for-hamletian-dilemma-411e0121ba1e | Decision Tree - Data Scientists magic bullet for Hamletian Dilemma | [
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Random Forest and Gradient Boosting
Anuja Nagpal
https://towardsdatascience.com/decision-tree-ensembles-bagging-and-boosting-266a8ba60fd9 | Decision Tree Ensembles- Bagging and Boosting | [
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My last blog focused on the concept of decision trees which form the basis of the Random Forest machine learning
Blake Lawrence
https://towardsdatascience.com/decision-trees-pruning-4241cc266fef | Decision TreesPruning | [
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Explainable AI or XAI is a sub-category of AI where the decisions made by the
Grant Holtes
https://towardsdatascience.com/decision-trees-understanding-explainable-ai-620fc37e598d | Decision TreesUnderstanding Explainable AI | [
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Everywhere you look people seem to be talking about one thing. Well, I mean apart from Donald Trump and his disturbingly entertaining antics. And thats AI. There are those that cant contain their excitement (Yo, AI is going to change the world!). There are those that are uncertain (We really dont yet
Shamli Prakash
htt... | Decoding AI | [
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Engineering a better Medium Stats experience with data science
Conor Dewey
https://towardsdatascience.com/deconstructing-metrics-on-medium-bf5b4863bf96 | Deconstructing Metrics on Medium | [
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Predicting the Rating a User would give a MovieA
Artem Oppermann
https://towardsdatascience.com/deep-autoencoders-for-collaborative-filtering-6cf8d25bbf1d | Deep Autoencoders For Collaborative Filtering | [
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A Generative Model is a powerful way of learning any kind of data distribution using unsupervised learning and it has
Prakash Pandey
https://towardsdatascience.com/deep-generative-models-25ab2821afd3 | Deep Generative Models | [
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Reflections on Coursera Specialization on Deep Learning by Andrew Ng
Richard Hackathorn
https://towardsdatascience.com/deep-issues-lurking-within-deep-learning-f923a96564c7 | Deep Issues Lurking Under Deep Learning: | [
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14 Jul 2015
Humphrey Sheil
https://towardsdatascience.com/deep-learning-and-machine-learning-c1101debe0c | Deep learning and machine learning | [
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Soil spectra to predict soil properties. A multitask
Jos Padarian
https://towardsdatascience.com/deep-learning-and-soil-science-part-1-8c0669b18097 | Deep learning and Soil Science - Part 1 | [
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dominated
George Seif
https://towardsdatascience.com/deep-learning-for-image-classification-why-its-challenging-where-we-ve-been-and-what-s-next-93b56948fcef | Deep Learning for Image Recognition: why its challenging, where weve been, and whats next | [
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When we think about the imminent development of the next digital revolution, humanity will face an unprecedented wave of automation. More and more smart and connected devices will coexist with us. This
Nelson Fernandez
https://towardsdatascience.com/deep-learning-for-machine-empathy-robots-and-humans-interaction-part-i... | Deep Learning for Machine Empathy: Robots and Humans InteractionPart I | [
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The 9th lesson in fast.ais Deep Learning course continues the dive into Generative
Wayne Nixalo
https://towardsdatascience.com/deep-learning-ii-l9-generative-models-dcd599ad6e0b | Deep Learning II L9: Generative Models | [
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I am writing this post as a follow up on a talk by the same name given at Re-work Deep Learning Summit, Singapore
Sonam Srivastava
https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03 | Deep Learning in Finance | [
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Use your webcam and Tensorflow.js to detect objects in real time.
Mike Shi
https://towardsdatascience.com/deep-learning-in-your-browser-a-brisk-guide-ca06c2198846 | Deep learning in your browser: A brisk guide | [
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Before telling you the answer to this question let me start with a short introduction about Deep Learning.
Rajat
https://towardsdatascience.com/deep-learning-made-easy-with-deep-learning-studio-complete-guide-a5c5ae58a771 | Deep Learning made easy with Deep Learning StudioComplete Guide | [
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Corporate intelligence is hard, and NAICS codes are terrible. Some companies buy lists of
Daniel Shapiro, PhD
https://towardsdatascience.com/deep-learning-magic-small-business-type-8ac484d8c3bf | Deep Learning Magic: Small Business Type | [
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A growing list of areas where machine learning is being applied for diagnosis based on medical imaging.
Neal Lathia
https://towardsdatascience.com/deep-learning-medical-diagnosis-c04d35fc2830 | Deep Learning & Medical Diagnosis | [
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Theory behind Restricted Boltzmann
Artem Oppermann
https://towardsdatascience.com/deep-learning-meets-physics-restricted-boltzmann-machines-part-i-6df5c4918c15 | Deep Learning meets Physics: Restricted Boltzmann Machines Part I | [
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Build your own Restricted
Artem Oppermann
https://towardsdatascience.com/deep-learning-meets-physics-restricted-boltzmann-machines-part-ii-4b159dce1ffb | Deep Learning meets Physics: Restricted Boltzmann Machines Part II | [
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Code for this project can be found on: Github.This article can also be found on my website here.
Moataz Elmasry
https://towardsdatascience.com/deep-learning-on-car-simulator-ff5d105744aa | Deep Learning on Car Simulator | [
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So you want a cheaper solution for running your deep learning code. AWS is reaming you with about 1K/month in bills, but your business logic really needs that deep learning magic. Worse yet, you cant just call an API to make it all go
Daniel Shapiro, PhD
https://towardsdatascience.com/deep-learning-on-the-digitalocean-... | Deep Learning on the DigitalOcean Stack? Not Quite Yet | [
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Scalable Deep Learning services are contingent on several constraints. Depending on your target application, you
Bharath Raj
https://towardsdatascience.com/deep-learning-on-the-edge-9181693f466c | Deep Learning on the Edge | [
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Doing cool things with data!
Priya Dwivedi
https://towardsdatascience.com/deep-learning-question-answer-model-with-demo-e21e43f60dd5 | Deep Learning QuestionAnswer model with demo | [
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In previous article (long ago, now I am back!!) I talked about overfitting and the problems faced due to overfitting. In this article I will discuss about one of the possible solution to prevent overfitting i.e. regularization (short notes from deeplearningbook.org
Tushar Gupta
https://towardsdatascience.com/deep-learn... | Deep Learning: Regularization Notes | [
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In the third part of our Deep Learning summary for 2017 we discuss the new discoveries and breakthroughs in reinforced learning and other fields.
Vladimir Fedak
https://towardsdatascience.com/deep-learning-summary-for-2017-reinforced-learning-and-miscellaneous-apps-18bfef0c5ab6 | Deep Learning summary for 2017: Reinforced Learning and Miscellaneous apps | [
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Deep Learning is disrupting many industries, and yours might not be an exception. Learn of the most notable deep learning projects of 2017 and ride the wave, or risk being rolled over
Vladimir Fedak
https://towardsdatascience.com/deep-learning-summary-for-2017-text-and-speech-applications-9ea02bb3835f | Deep Learning summary for 2017: Text and Speech Applications | [
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Below is a distilled collection of conversations, messages, and debates Ive had with peers and students on
Jonathan Balaban
https://towardsdatascience.com/deep-learning-tips-and-tricks-1ef708ec5f53 | Deep Learning Tips and Tricks | [
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Over the past several years, deep learning has become the go-to technique for most
George Seif
https://towardsdatascience.com/deep-learning-vs-classical-machine-learning-9a42c6d48aa | Deep Learning vs Classical Machine Learning | [
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First part on a full discussion on how to do Distributed Deep Learning with Apache Spark. This part: What is Spark, basics on Spark+DL and a little more. You can
Favio V zquez
https://towardsdatascience.com/deep-learning-with-apache-spark-part-1-6d397c16abd | Deep Learning With Apache SparkPart 1 | [
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Second part on a full discussion on how to do Distributed Deep Learning with Apache Spark. I will focus entirely on the DL pipelines library and how to use it from
Favio V zquez
https://towardsdatascience.com/deep-learning-with-apache-spark-part-2-2a2938a36d35 | Deep Learning With Apache SparkPart 2 | [
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This article will be a bit different than my usual business-oriented articles. In a recent
Daniel Shapiro, PhD
https://towardsdatascience.com/deep-learning-with-digitalocean-redux-e6f447e64c75 | Deep Learning with DigitalOcean: Redux | [
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The human brain imitation.
Vihar Kurama
https://towardsdatascience.com/deep-learning-with-python-703e26853820 | Deep Learning with Python | [
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I started this article with the hopes of confronting a few misconceptions about Deep
Jesse Moore
https://towardsdatascience.com/deep-misconceptions-about-deep-learning-f26c41faceec | Deep Misconceptions About Deep Learning | [
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One area that Deep Learning has not explored extensively is the uncertainty in estimates. Most Deep Learning
Sachin Abeywardana
https://towardsdatascience.com/deep-quantile-regression-c85481548b5a | Deep Quantile Regression | [
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A key challenge in deep learning is how to get estimates on the bounds of predictors. Quantile regression, first introduced in the 70s by Koenker and Bassett [1], allows us to estimate percentiles of the underlying conditional data distribution even in cases
Jacob Zweig
https://towardsdatascience.com/deep-quantile-regr... | Deep Quantile Regression in Tensorflow | [
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Detecting Violence with Neural Networks
Sebastian Kwiatkowski
https://towardsdatascience.com/deep-surveillance-6b389abeaf95 | Deep Surveillance | [
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#4 Research Paper Explained
SAGAR SHARMA
https://towardsdatascience.com/deepminds-playing-capture-the-flag-with-deep-reinforcement-learning-a9f71256442e | DeepMinds Playing Capture The Flag with Deep Reinforcement Learning | [
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DeepSchool.io is an open-source, community based project to teach the A-Z of Deep Learning
Sachin Abeywardana
https://towardsdatascience.com/deepschool-io-deep-learning-learning-ce4385a8978c | DeepSchool.io: Deep Learning Learning | [
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Scene (Harry Potter reference) - Dumbledore wields a wand
Ashik Poovanna
https://towardsdatascience.com/defence-against-the-data-arts-python-v-s-r-5f4529c1d90f | Defence Against the Data Arts : Python v/s R | [
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This topic was covered in last week Data Science Office hours session.
Irshad Muhammad
https://towardsdatascience.com/defining-a-data-science-problem-28c21d817c0b | Defining a Data Science problem | [
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Demystifying CryptoCurrency Price
Chalita Lertlumprasert
https://towardsdatascience.com/demystifying-cryptocurrency-price-prediction-5fb2b504a110 | Mirror, Mirror on the Wall, Will Crypto Prices Rise or Fall? | [
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In this tutorial (derived from my original post here), you will learn what
Stefan Hosein
https://towardsdatascience.com/demystifying-generative-adversarial-networks-c076d8db8f44 | Demystifying Generative Adversarial Networks | [
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Original DenseNet paper: https://arxiv.org/pdf/1608.06993v3.pdf
Manish Chablani
https://towardsdatascience.com/densenet-2810936aeebb | DenseNet | [
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Learn how to deploy your model to production
Francesco Zuppichini
https://towardsdatascience.com/deploy-tensorflow-models-9813b5a705d5 | Deploy TensorFlow models | [
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0.32470831274986267,
-0.15536950528621674,
0.07194358855... |
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