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Step-by-step example how to build a reasonable Scala library to
Kirill Panarin
https://towardsdatascience.com/serving-tensorflow-model-in-scala-6caeadbb2d55 | Serving TensorFlow model in Scala | [
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Learn about the various options you have to setup a data science environment with Python, R, Git, and Unix Shell on your local computer.
Michael Galarnyk
https://towardsdatascience.com/setup-a-data-science-environment-on-your-personal-computer-6ce931113914 | Setup a Data Science Environment on your Personal Computer | [
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Machine Learning and Artificial Intelligence have been buzzing for a couple of
Nabeel Abdul Latheef
https://towardsdatascience.com/shaping-up-e-commerce-with-machine-learning-d64fa7b2e546 | Shaping up E-Commerce with Machine Learning | [
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AWS recently announced SageMaker, which helps you do everything from building models from scratch to
Zak Jost
https://towardsdatascience.com/sharing-your-sagemaker-model-eaa6c5d9ecb5 | Sharing Your SageMaker Model | [
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In part 1 Shift left: empowerment as-a-service, we looked at the ability of shift left to bring IT services closer to employees via lower touch, lower cost delivery channels. Deciding to implement shift left is only
Rob Young
https://towardsdatascience.com/shift-left-empowerment-as-a-service-part-2-ai-driven-automation... | Shift left: empowerment as-a-service part 2 AI-driven automation | [
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Use a marketer approach for better results
Tricia Aanderud
https://towardsdatascience.com/should-data-stories-inform-or-persuade-2753330f3f37 | Should Data Stories Inform or Persuade? | [
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The Concierge vs. the Wizard of Oz MVP
Chris Butler
https://towardsdatascience.com/should-your-customers-be-conned-by-a-human-or-ai-6a87fbecdefe | Should your customers be conned by a human or AI? | [
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Introduction
Rohith Gandhi
https://towardsdatascience.com/siamese-network-triplet-loss-b4ca82c1aec8 | Siamese Network & Triplet Loss | [
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When I found out about FATAs illness during ESL One Genting, it was the middle of the
Elvan Aydemir
https://towardsdatascience.com/simulating-ti-qualifications-through-dpc-c994aa780cca | Simulating TI Qualifications Through DPC | [
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Tired of trying to meet with someone and never find a date or time? Me too.
Favio V zquez
https://towardsdatascience.com/skejul-meetings-with-deep-learning-5efab285b111 | Skejul meetings with Deep Learning | [
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Lets talk about bit packing, deduplication and many more
Maxim Zaks
https://towardsdatascience.com/smart-way-of-storing-data-d22dd5077340 | Smart way of storing data | [
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Attention: I would like to point out that I come to this topic as a practitioner of machine
Sebastian Kwiatkowski
https://towardsdatascience.com/smells-like-machine-learning-progress-611a2851acec | Smells Like Machine Learning Progress | [
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The Mark of Great Data Scientist is perhaps implementing ML
Venkat Raman
https://towardsdatascience.com/so-how-many-ml-models-you-have-not-built-e692f549b163 | So, How Many ML Models You Have NOT Built? | [
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This is the third post in a series of three looking at how technology is shaping our social connections. The first post tried to convince you that our online and offline social networks are incredibly important. The second
Jimmy Tidey
https://towardsdatascience.com/social-network-data-twitter-vs-fb-vs-google-vs-everyon... | Social network data: Twitter vs FB vs Google vs everyone else | [
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Layered Architecture
Anuradha Wickramarachchi
https://towardsdatascience.com/software-architecture-patterns-98043af8028 | Software Architecture Patterns | [
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Prove your genius the lazy way.
Kasper Fredenslund
https://towardsdatascience.com/solving-only-1-can-answer-this-problems-with-machine-learning-e016594c5cbd | Solving only 1% can answer this Problems With Machine Learning | [
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The multi-armed bandit problem is a classic reinforcement learning example where we are
Anson Wong
https://towardsdatascience.com/solving-the-multi-armed-bandit-problem-b72de40db97c | Solving the Multi-Armed Bandit Problem | [
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Some useful advice and Q/A for machine
Tirthajyoti Sarkar
https://towardsdatascience.com/some-useful-advice-and-q-a-for-machine-learning-data-science-starters-part-i-54f8abd531d5 | Essential beginners' Q/A for machine learning/data science | [
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Project by Mohamed Nasreldin, Stephen Ma, Eric Dailey, Phuc Dang
Mohamed Nasreldin
https://towardsdatascience.com/song-popularity-predictor-1ef69735e380 | Song Popularity Predictor | [
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My experiences in the Wild
Tricia Aanderud
https://towardsdatascience.com/sorry-folks-excel-is-not-an-enterprise-reporting-solution-af6da19d2b81 | Sorry Folks! Excel is Not an Enterprise Reporting Solution | [
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We all face the problem of spams in our inboxes. Lets build a spam classifier program in
Tejan Karmali
https://towardsdatascience.com/spam-classifier-in-python-from-scratch-27a98ddd8e73 | Spam Classifier in Python from scratch | [
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I still remember my first day in machine learning class. The first example which was
Natasha Sharma
https://towardsdatascience.com/spam-detection-with-logistic-regression-23e3709e522 | Spam Detection with Logistic Regression | [
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The big picture of what Spark +AI Summit was all about came from the master of big picture painting - Marc Andreessen. His firm
Sergey Zelvenskiy
https://towardsdatascience.com/spark-ai-summit-2018-overview-7c5a8d7be296 | Spark + AI Summit 2018Overview | [
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Clustering is one of the most widely used techniques for exploratory data analysis. Its goal is to
Amine Aoullay
https://towardsdatascience.com/spectral-clustering-for-beginners-d08b7d25b4d8 | Spectral Clustering for beginners | [
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The majority of Raspberry Pi speech-to-text examples shared online seem to rely on various
Mike Alatortsev
https://towardsdatascience.com/speech-recognition-on-raspberry-pi-3-b-8351c418dc25 | Speech recognition on Raspberry Pi 3 B | [
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MLaaS Part 2: Speaker on the wall, whos got the best voice of them all?
Sebastian Kwiatkowski
https://towardsdatascience.com/speech-synthesis-as-a-service-5c65d17e62f4 | Speech Synthesis as a Service | [
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Broadcasting makes it possible to vectorize
Marko Cotra
https://towardsdatascience.com/speed-up-your-python-code-with-broadcasting-and-pytorch-64fbd31b359 | Speed Up Your Python Code With Broadcasting and PyTorch | [
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An overview of methods to speed up training of convolutional neural networks without
Alex Burlacu
https://towardsdatascience.com/speeding-up-convolutional-neural-networks-240beac5e30f | Speeding up Convolutional Neural Networks | [
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DIY with Examples and Sample Code
Vijini Mallawaarachchi
https://towardsdatascience.com/sql-cheat-sheet-for-interviews-6e5981fa797b | SQL Recap for Interviews | [
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This series focuses on the most frequent data science and analytical problems in the real-world, and aims at solving them with SQL.
Sejal Vaidya
https://towardsdatascience.com/sql-in-a-nutshell-part-1-basic-real-world-scenarios-33a25ba8d220 | SQL in a Nutshell: Part 1Basic Real-World Scenarios | [
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A guide for those in business, marketing or strategy roles in tech.
Will Lawrence
https://towardsdatascience.com/sql-the-one-technical-skill-all-non-technicals-need-to-know-843db07d9bc8 | SQL: The one technical skill all non-technicals need to know | [
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Setting a new state of the art on ImageNet
Paul-Louis Pr ve
https://towardsdatascience.com/squeeze-and-excitation-networks-9ef5e71eacd7 | Squeeze-and-Excitation Networks | [
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I spoke in a Webinar this past Saturday about how to get into Data Science. One of the questions asked
Kristen Kehrer
https://towardsdatascience.com/starting-a-data-science-project-993256c41b77 | Starting a Data Science Project | [
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Last week we discussed the burgeoning growth of AI systems. We saw several examples of how those systems are impacting our lives more and more. I made the case that we ought to focus more on reliability when making architecture choices. After all, peoples lives
James Bowen
https://towardsdatascience.com/starting-out-wi... | Starting out with Haskell Tensor Flow | [
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For a person being from a non-statistical background the most confusing aspect of
vibhor nigam
https://towardsdatascience.com/statistical-tests-when-to-use-which-704557554740 | Statistical TestsWhen to use Which ? | [
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In this story, we will learn some image processing concepts and how to hide an
Kelvin Salton do Prado
https://towardsdatascience.com/steganography-hiding-an-image-inside-another-77ca66b2acb1 | Steganography: Hiding an image inside another | [
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How to use simple Python libraries and
Tirthajyoti Sarkar
https://towardsdatascience.com/step-by-step-guide-to-build-your-own-mini-imdb-database-fc39af27d21b | Step-by-step guide to build your own mini IMDB database | [
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This is part 2 of my series on optimization algorithms used for training neural
Vitaly Bushaev
https://towardsdatascience.com/stochastic-gradient-descent-with-momentum-a84097641a5d | Stochastic Gradient Descent with momentum | [
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Exploring financial data with object-oriented programming and additive models
William Koehrsen
https://towardsdatascience.com/stock-analysis-in-python-a0054e2c1a4c | Stock Analysis in Python | [
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Make (and lose) fake fortunes while learning real Python
William Koehrsen
https://towardsdatascience.com/stock-prediction-in-python-b66555171a2 | Stock Prediction in Python | [
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There is a really big problem today using machine
Aaron Edell
https://towardsdatascience.com/stop-running-face-recognition-until-youve-read-this-92d6b94f0fa1 | Stop running face recognition until youve read this | [
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One of the key ways military strategy has been taught in the US is according to the formula Strategy = ends
Robert de Graaf
https://towardsdatascience.com/strategy-for-data-scientists-e35aebe38461 | Strategy for Data Scientists | [
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My Search for a Deep Learning Principia
Utkarsh Saxena
https://towardsdatascience.com/strongly-typed-recurrent-neural-networks-f84772696a86 | Strongly-Typed Recurrent Neural Networks | [
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Completing a machine learning project
Jan Zawadzki
https://towardsdatascience.com/structuring-your-machine-learning-project-course-summary-in-1-picture-and-22-nuggets-of-wisdom-95b051a6c9dd | 22 nuggets of wisdom to structure your machine learning project | [
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A lot of our lives, both our working lives and our personal lives, are spent doing repetitive, uncreative tasks. Many of these tasks are enjoyable: they include hobbies like gardening or baking that we enjoy for hard-to-articulate reasons. But, they also include things we
Seth Weidman
https://towardsdatascience.com/sud... | Sudoku and Doing Your Best Work | [
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Hi folks, I hope you all are doing well. In todays edition we will try to understand in short about Goodness of fit. This blog consist of basic understanding regarding the topic along with it the way to evaluate a model. So all the folks who are really keen about knowing this
Madhav Mishra
https://towardsdatascience.co... | Summarizing Goodness Of Fit | [
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Its May 2015, and rescue teams are working to rebuild Nepal following the April
Gabriel Tseng
https://towardsdatascience.com/summarizing-tweets-in-a-disaster-part-ii-67db021d378d | Summarizing Tweets in a Disaster (part II) | [
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Last year was very intense for the cTuning foundation and dividitiwe continued working closely with AI, ML and systems communities to automate experimentation while improving reproducibility and reusability of
Grigori Fursin
https://towardsdatascience.com/summary-of-2017-activities-related-to-open-and-reproducible-rese... | Summary of 2017 activities related to open and reproducible research | [
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Why Artificial Intelligence and Machine Learning ?
Vihar Kurama
https://towardsdatascience.com/supervised-learning-with-python-cf2c1ae543c1 | Supervised Learning with Python | [
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Understanding the differences between the two main types of
Devin Soni
https://towardsdatascience.com/supervised-vs-unsupervised-learning-14f68e32ea8d | Supervised vs. Unsupervised Learning | [
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There are multiple ways to classify data with machine learning. You could run a logistic regression, use decision trees, or build a neural network to accomplish the task. In 1963, Vladimir Vapnik and Alexey Chervonenkis developed another classification
Aakash Tandel
https://towardsdatascience.com/support-vector-machine... | Support Vector MachinesA Brief Overview | [
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Comparison with logistic regression and hinge loss
Ravindra Kompella
https://towardsdatascience.com/support-vector-machines-intuitive-understanding-part-1-3fb049df4ba1 | Support vector machines ( intuitive understanding )Part#1 | [
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Symbolic regression and genetic programming are nowhere close to being mainstream
Jan Krepl
https://towardsdatascience.com/symbolic-regression-and-genetic-programming-8aed39e7f030 | Symbolic Regression and Genetic Programming | [
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Stop trying to put all knowledge in your head. Your brain is a terrible storage medium for information. Put it where it belongs: in the software. And learn how to use it.
Jurgen Appelo
https://towardsdatascience.com/taxi-to-funkhaus-2dfee80f9427 | Taxi to Funkhaus | [
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This is the first project of Term 3 of the Udacity Self-Driving Car Engineer
Eddie Forson
https://towardsdatascience.com/teaching-cars-to-drive-highway-path-planning-109c49f9f86c | Teaching Cars To DriveHighway Path Planning | [
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Recently, my thinking has circulated around what feel like some of Machine Learnings biggest meta-conversations: the potential and limitations of learning a generally intelligent actor, the nuance and genuine normative challenge of
Cody Marie Wild
https://towardsdatascience.com/tell-me-a-story-thoughts-on-model-interpr... | Tell Me a Story: Thoughts on Model Interpretability | [
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Everything you need to know
SAGAR SHARMA
https://towardsdatascience.com/tensorflow-1-9-has-arrived-1e6e9171ce5e | TensorFlow 1.9 has Arrived! | [
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By Priya Dwivedi, Data Scientist @ SpringML
SpringML
https://towardsdatascience.com/tensorflow-for-manufacturing-quality-control-bc1bc6740558 | Tensorflow for Manufacturing Quality Control | [
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Deep learning can solve many interesting problems that seems impossible for human, but this
Keshav Aggarwal
https://towardsdatascience.com/tensorflow-image-augmentation-on-gpu-bf0eaac4c967 | Tensorflow Image: Augmentation on GPU | [
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On CPU with Inception-v3(In seconds)
SAGAR SHARMA
https://towardsdatascience.com/tensorflow-image-recognition-python-api-e35f7d412a70 | TensorFlow Image Recognition Python API Tutorial | [
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TensorFlow is a library which can be applied to all the machine learning algorithms especially
Nidhin Mahesh
https://towardsdatascience.com/tensorflow-no-idea-where-to-begin-b7b981d7321e | TensorFlow : No idea where to begin? | [
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This week I sat down with my fellow Developer Advocate and all-around awesome person Sara
Yufeng G
https://towardsdatascience.com/tensorflow-object-detection-in-action-4aca394d51b1 | TensorFlow Object Detection in Action | [
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What do we get with it?
SAGAR SHARMA
https://towardsdatascience.com/tensorflow-on-mobile-tensorflow-lite-a5303eef77eb | TensorFlow on Mobile: TensorFlow Lite | [
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On Android and iOS
SAGAR SHARMA
https://towardsdatascience.com/tensorflow-on-mobile-tutorial-1-744703297267 | TensorFlow on Mobile: Tutorial | [
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In previous articles we analyzed objects in images using TensorFlow Object Detection API applying different types of models. (Article 1, Article 2)
Nicolas Bortolotti
https://towardsdatascience.com/tensorflow-photo-x-ray-object-detection-with-app-engine-7de9dd8f63f5 | TensorFlow Photo x-Ray Object Detection with App Engine | [
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Quick Note: I will not be predicting the stock price of Tesla. But I will try.
Dale Wahl
https://towardsdatascience.com/tesla-stock-price-prediction-f16a702f67d7 | Tesla: Stock Price Prediction | [
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After graduating from General Assemblys Data Science Immersive Course, Im proud to announce that Ive started a new position as a Data Scientist for the Mayors Office of Budget and Innovation with the City Of Los Angeles. Im a few weeks into the position, and Im focused on improving LAs city services using
Brendan Baile... | Test Me | [
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Ive spent the last 6 years of my life heavily involved in testing. Whether it was the performance of an
Kristen Kehrer
https://towardsdatascience.com/testing-to-learn-part-1-16a7968d2ba3 | Using Hypothesis Tests to Learn | [
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The 2018 Conference on Computer Vision and Pattern Recognition (CVPR) took place last week in
George Seif
https://towardsdatascience.com/the-10-coolest-papers-from-cvpr-2018-11cb48585a49 | The 10 coolest papers from CVPR 2018 | [
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I have been actively focussing on specialising Deep Learning for the last 2 years. My personal interest towards Deep learning started around 2015 when Google open sourced Tensorflow .Tried quickly couple of examples from the Tensorflow documentation and left with
Vishnu Subramanian
https://towardsdatascience.com/the-3-... | The 3 popular courses on DeepLearning | [
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Avoiding these common mistakes wont get you hired. But not avoiding them guarantees your application a one-way ticket to the no pile.
Jeremie Harris
https://towardsdatascience.com/the-4-fastest-ways-not-to-get-hired-as-a-data-scientist-565b42bd011e | The 4 fastest ways not to get hired as a data scientist | [
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The First in a Series on Deep Learning for
Seth Weidman
https://towardsdatascience.com/the-5-deep-learning-breakthroughs-you-should-know-about-df27674ccdf2 | The 4 Deep Learning Breakthroughs You Should Know About | [
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tldr: The A[?] Bug affecting iPhone users may have been a
Nick Locascio
https://towardsdatascience.com/the-a-iphone-bug-spread-like-a-virus-8731f447b959 | The A [?] iPhone Bug Spread Like a Virus | [
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How Algorithms are going to change the Payments Industry
Dwayne Gefferie
https://towardsdatascience.com/the-algorithmization-of-payments-how-algorithms-are-going-to-change-the-payments-industry-5dd3f266d4c3 | The Algorithmization of Payments | [
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There are a few technologies today that I think are going to massively reshape the
Shanif Dhanani
https://towardsdatascience.com/the-amazing-impact-of-reinforcement-learning-7a98ff553ac5 | The Amazing Impact of Reinforcement Learning | [
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Strategies for Effective Data Visualization
DipanjanDJ) Sarkar
https://towardsdatascience.com/the-art-of-effective-visualization-of-multi-dimensional-data-6c7202990c57 | The Art of Effective Visualization of Multi-dimensional Data | [
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A beginners account of getting into comfort zone of learning
Aparna C Shastry
https://towardsdatascience.com/the-art-of-learning-data-science-65b9f703f932 | The Art of Learning Data Science | [
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With all the excitement surrounding data and machine learning its easy to forget just how
Sean McClure
https://towardsdatascience.com/the-art-of-making-intelligent-machines-e024e2d170d6 | The Art of Making Intelligent Machines | [
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When we think about datasets, we naturally think in row based form, where row is an entry and
Maxim Zaks
https://towardsdatascience.com/the-beauty-of-column-oriented-data-2945c0c9f560 | The beauty of column-oriented data | [
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Every neural network has to train its weights and biases to
Chi-Feng Wang
https://towardsdatascience.com/the-beginners-guide-to-gradient-descent-c23534f808fd | The Beginner's Guide to Gradient Descent | [
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Putting Pen to Paper
Vega Intelligent Solutions
https://towardsdatascience.com/the-beginning-of-something-great-the-vega-intelligent-design-5e43c1512a6d | The Beginning of Something Great: The Vega Intelligent Design | [
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A year ago, I dropped out of grad school to co-found a startup with my brother. Our goal was simple enough: fix the data science talent shortage.
Jeremie Harris
https://towardsdatascience.com/the-best-data-scientists-arent-being-discovered-22deff8ec002 | The best data scientists arent being discovered. | [
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Imitating Donald Trumps Style Using Recurrent Neural Networks
Leon Zhou
https://towardsdatascience.com/the-best-words-cf6fc2333c31 | The Best Words | [
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Determining the Business Demand for Data, Information and Analytics
Dwayne Gefferie
https://towardsdatascience.com/the-big-bang-of-data-6dce91ff12cf | The Big Bang of Data | [
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50+ interviews worth of comprehensive data science resources
Conor Dewey
https://towardsdatascience.com/the-big-list-of-ds-ml-interview-resources-2db4f651bd63 | The Big List of DS/ML Interview Resources | [
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The title speaks volumes on the issue of fitting of models in machine learning. Man
Raghu Raj Rai
https://towardsdatascience.com/the-capricious-models-of-machine-learning-23cd2f36dbbe | The Capricious Models of Machine Learning | [
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The rise of artificial intelligence is grounded in the success of deep learning
Susan Li
https://towardsdatascience.com/the-complete-guide-on-learning-deep-learning-72cabb30d721 | The Complete Guide on Learning Deep Learning | [
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From National Chicken Wings Day to National Dress Up Your Pet Day to National
Hannah Yan Han
https://towardsdatascience.com/the-complete-guide-to-superfluous-holidays-7be26f0a86db | The Complete Guide to Superfluous Holidays | [
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Unless you are living under a rock, you would have come across plethora of articles convincing you that the AI revolution has come and it is here to stay. While we try to understand some of the theory behind the claims made, there would be many more
Santosh GSK
https://towardsdatascience.com/the-current-trends-in-artif... | The current trends in Artificial Intelligence | [
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We are used to jumping to conclusions really fast, without analyzing all sides. As such, when trying to understand the world, intuition frequently fails. Here I
Favio V zquez
https://towardsdatascience.com/the-curse-of-intuition-in-data-science-552bc28c55e5 | The curse of intuition in Data Science | [
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Healthcare is notorious for its lack of adopted data formats. The one exception is the
Leonard D'Avolio PhD
https://towardsdatascience.com/the-dangers-of-claims-based-on-claims-142fd2c9f7cd | The Dangers of Claims Based on Claims | [
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Emojis and data are two of my favorite things and I have been itching to combine them in a
Christine Quan
https://towardsdatascience.com/the-data-files-twitter-emoji-analysis-987093f9c1ee | Twitter Emoji Analysis: An Airbnb Story | [
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Whats the difference between Machine Learning, Artificial Intelligence, Deep Learning, and Data
Ofer Egozi
https://towardsdatascience.com/the-data-product-scientist-manager-469cc1d21f9 | The Data-Product-Scientist-Manager | [
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Both in demand and well paid, it looks ideal for both students on the hunt for job security and workers seeking better pay. Advice to acquire data science
Kirill Eremenko
https://towardsdatascience.com/the-data-science-gap-5cc4e0d19ee3 | The Data Science Gap | [
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Ever struggle to recall what Adam, ReLU or YOLO mean? Look no further and check out every term you need to master Deep Learning.
Jan Zawadzki
https://towardsdatascience.com/the-deep-learning-ai-dictionary-ade421df39e4 | The Deep Learning(.ai) Dictionary | [
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A glimpse into the world of informative graphical beauties
Aman Saxena
https://towardsdatascience.com/the-design-of-statistical-graphics-5265485e9bb5 | The Design of Statistical Graphics | [
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Its fair to say that a lot of us are singing along with todays largest Latin and Reggaeton
Bo Plantinga
https://towardsdatascience.com/the-diffusion-of-latin-and-reggaeton-69113f9929dd | The diffusion of Latin and Reggaeton | [
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When it comes to conveying information to your audience, charts are a simple and effective way to
Payman Taei
https://towardsdatascience.com/the-dos-and-don-ts-of-chart-making-13c629456027 | The Dos and Donts of Chart Making | [
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In the era of digital transformation, AI will deliver change in all type organizations
Felipe Sanchez
https://towardsdatascience.com/the-drivers-of-ai-business-transformation-941c5c4bc685 | The drivers of AI Business Transformation | [
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A simple 3-step system for Data Scientists to leave an impression
Conor Dewey
https://towardsdatascience.com/the-edge-you-need-at-your-next-interview-c8cb0ab53da | The Edge You Need at Your Next Interview | [
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-0.2277778... |
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