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Factfulness
Vivian Zheng
https://towardsdatascience.com/making-great-hypothesis-588f93f52206 | The Making of Great Hypothesis | [
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Open-source software brings together many altruistic programmers that freely
Marc Laforet
https://towardsdatascience.com/making-my-first-open-source-software-contribution-8ebf622be33c | My first contribution to open-source software | [
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So youre planning to read the whole article? Lets see
Miha Gazvoda
https://towardsdatascience.com/man-plans-god-laughs-the-planning-fallacy-ea9bcacc16f4 | Man Plans, God Laughs: The Planning Fallacy | [
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Reproducibility, good management and tracking experiments is necessary for making easy to test others work and analysis. In this first part we
Favio V zquez
https://towardsdatascience.com/manage-your-machine-learning-lifecycle-with-mlflow-part-1-a7252c859f72 | Manage your Machine Learning Lifecycle with MLflowPart 1. | [
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Working with Deep Learning involves running innumerable experiments to test various
Anant Gupta
https://towardsdatascience.com/managing-experimentation-in-deep-learning-ca6db050b104 | Managing Experimentation in Deep Learning | [
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Teaching computers to draw new and original manga and anime faces with DCGANs
TD
https://towardsdatascience.com/mangagan-8362f06b9625 | MangaGAN | [
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What an analysis of 1M+ articles can tell us about modern neuroscience research
Fahd Alhazmi
https://towardsdatascience.com/mapping-the-landscape-of-neuroscience-s-bc14628e8713 | Mapping The Landscape of Neuroscience(s) | [
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A way to explore current market conditions is to compare today with similar periods in
Grant Holtes
https://towardsdatascience.com/market-evaluation-with-similarity-methods-e50eacca34b9 | Market Evaluation with similarity methods | [
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A primer on Market Mix Modeling.
Ridhima Kumar
https://towardsdatascience.com/market-mix-modeling-mmm-101-3d094df976f9 | Market Mix Modeling (MMM)101 | [
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A Complete Real-World Implementation
William Koehrsen
https://towardsdatascience.com/markov-chain-monte-carlo-in-python-44f7e609be98 | Markov Chain Monte Carlo in Python | [
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A Machine Learning case study on the women of Marvel
TD
https://towardsdatascience.com/marvelous-women-b9a64745fe3b | Marvelous Women | [
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Using VC dimension to gauge an algorithms
Devin Soni
https://towardsdatascience.com/measuring-the-power-of-a-classifier-c765a7446c1c | Measuring the Power of a Classifier With VC Dimension | [
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Generously, Medium analytics are spartan. Whether youre an individual writer or a publication, they give you
Emma Townley-Smith
https://towardsdatascience.com/medium-analytics-a-wishlist-39120a8c27e9 | Medium Analytics: A Wishlist | [
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Lessons and takeaways from a first month writing Data articles on Medium
Finn Qiao
https://towardsdatascience.com/medium-or-how-i-learned-to-stop-worrying-and-love-the-blog-5d6de7a7a20e | Medium or: How I Learned to Stop Worrying and Love the Blog | [
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If you can afford so many hours of AWS P2 instances, this post may not be the right one for you to read.
Labeeb Ibrahim
https://towardsdatascience.com/meeting-challenges-in-pursuing-a-career-in-deep-learning-7cd55c5cf304 | Meeting Challenges in pursuing a career in Deep Learning | [
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Shab Dev Story #02
Eyy b Sari
https://towardsdatascience.com/meme-search-using-pretrained-word2vec-9f8df0a1ade3 | Meme search using pretrained word2vec | [
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Analysis of gender differences in
Ludi Rehak
https://towardsdatascience.com/men-vs-women-comparing-mediums-most-popular-stories-by-gender-23e0767252d | Men vs Women: Comparing Mediums most popular stories by Gender | [
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Do you remember learning about linear regression in your Statistics class? Congratulations
Dror Berel
https://towardsdatascience.com/meta-machine-learning-packages-in-r-c3e869b53ed6 | [
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Daniel Yarmoluk, Director of IoT and Data Science, ATEK, All Things Data Podcast and VertiAI
Daniel Yarmoluk
https://towardsdatascience.com/metadata-management-as-a-strategic-imperative-88a16c6ec731 | Metadata Management as a Strategic Imperative | [
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The first week of Metis focused mainly on the use of the Python library pandasthe go-to tool for data scientists to
Derick Liang
https://towardsdatascience.com/metis-introduction-5e772c8affad | METIS INTRODUCTION | [
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Simple steps to neuromal health
Nicholas Mayhew
https://towardsdatascience.com/mind-coding-99acd368d36d | Mind-coding | [
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Which countries contribute the most to research in high energy physics
Ugo Bertello
https://towardsdatascience.com/mining-the-hep-inspire-database-77a68950ef59 | Mining the HEP-Inspire database | [
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The American Dental Association has called for its members to help fight against
Jenny Listman
https://towardsdatascience.com/mississippi-dental-opioid-epicenter-of-2014-ab4d7f68fa49 | Mississippi: Dental Opioid Epicenter of 2014 | [
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This blog post introduces an open source Python package for implementing mixed effects
Sourav Dey
https://towardsdatascience.com/mixed-effects-random-forests-6ecbb85cb177 | Mixed Effects Random Forests in Python | [
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Artificial intelligence is trying to learn how to learn from the way humans
Firdaouss Doukkali
https://towardsdatascience.com/model-agnostic-meta-learning-maml-8a245d9bc4ac | What is Model-Agnostic Meta-learning (MAML) ? | [
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I spoke with a Data Scientist at a meetup recently that mentioned he had found building models from scratch intellectually rewarding. Noting it gave him great intuition on the behavior of the models and was also a good OOP project. I found that by dedicating a few
Geoff Counihan
https://towardsdatascience.com/model-ove... | Model overviews and code from scratch | [
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(for non-technical people)
Ioannis Kalfas
https://towardsdatascience.com/modeling-visual-neurons-with-convolutional-neural-networks-e9c01ddfdfa7 | Modeling Visual Neurons with Convolutional Neural Networks | [
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Have you ever wondered how life formed from the primordial soup and evolved to the
Vijini Mallawaarachchi
https://towardsdatascience.com/molecular-phylogenetics-using-bio-phylo-57ce27492ee9 | Molecular Phylogenetics using Bio.Phylo | [
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Stop Trying To Load Into PandasAnd Just Load Into Pandas
Lockefox
https://towardsdatascience.com/mongodb-vs-pandas-5abe2c5ff6f3 | MongoDB vs Pandas | [
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MongoDB World 18 shows us the future of database technology
Sohan Choudhury
https://towardsdatascience.com/mongodb-world-18-leading-the-nosql-charge-b6032116f31f | MongoDBLeading the NoSQL Charge | [
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MCTS For Every Data Science Enthusiast
SAGAR SHARMA
https://towardsdatascience.com/monte-carlo-tree-search-158a917a8baa | Monte Carlo Tree Search | [
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Apache Spark is quickly gaining steam both in the headlines and real-world
Susan Li
https://towardsdatascience.com/multi-class-text-classification-with-pyspark-7d78d022ed35 | Multi-Class Text Classification with PySpark | [
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Predicting sequential data from categorical features only
Kwyk
https://towardsdatascience.com/multi-state-lstms-for-categorical-features-66cc974df1dc | Multi-state LSTMs for categorical features | [
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In this blog, I will be explaining about image to image translation which is popularly known as BicycleGAN. The task of image to image translation can be thought of as per pixel regression or classification. One more approach that can be used to solve this problem
Prakash Pandey
https://towardsdatascience.com/multimoda... | Multimodal Image-to-Image Translation | [
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Sequence Alignment of 3 or more
Vijini Mallawaarachchi
https://towardsdatascience.com/multiple-sequence-alignment-using-clustal-omega-and-t-coffee-3cc662b1ea82 | Multiple Sequence Alignment using Clustal Omega and T-Coffee | [
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How ignoring the grammar of graphics can wreck even
Ganes Kesari
https://towardsdatascience.com/murdering-a-legendary-data-story-what-can-we-learn-from-a-grammar-of-graphics-ad6ca42f5e30 | What are the Ingredients of a Terrible Data Story? | [
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Deep Learning meets Interactive Evolutionary Computation
Irhum Shafkat
https://towardsdatascience.com/music-by-means-of-natural-selection-11934d7e89a3 | Music by means of natural selection | [
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While controversy is raging on how private data are collected and used and while
Jean-Baptiste Hironde
https://towardsdatascience.com/music-targeting-the-new-eldorado-for-brands-48590a0b7108 | Music targeting: the new Eldorado for brands? | [
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Introduction
Brian Mwangi.
https://towardsdatascience.com/my-advice-to-an-aspiring-data-scientist-2ace6bd5cbe6 | Advice To An Aspiring Data Scientist. | [
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At the point of writing, it was the day before the last day of my Data Scientist internship at
Admond Lee
https://towardsdatascience.com/my-first-data-scientist-internship-7f7aa2ee4040 | My First Data Scientist Internship | [
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Artificial Intelligence is the buzz word right now and as somebody who is into data science, I have been
Jahnavi Mahanta
https://towardsdatascience.com/my-interpretation-of-ai-a6eed63e4cb9 | My interpretation of AI | [
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I still learn new knowledge everyday with my growing passion in Data Science field. To
Admond Lee
https://towardsdatascience.com/my-journey-from-physics-into-data-science-5d578d0f9aa6 | My Journey from Physics into Data Science | [
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In this post Ill share how Ive been studying Deep Learning and using it to solve data science problems
Favio V zquez
https://towardsdatascience.com/my-journey-into-deep-learning-c66e6ef2a317 | My journey into Deep Learning | [
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I am a first-year graduate student at New York University, pursuing Computer Science. I
Ilyas Habeeb
https://towardsdatascience.com/my-journey-into-machine-learning-class-1-43a003f69666 | My Journey into Machine Learning: Class 1 | [
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Hey, everyone! Thanks for joining me on this amazing journey of exploring Machine
Ilyas Habeeb
https://towardsdatascience.com/my-journey-into-machine-learning-class-2-554ae5fa8255 | My Journey into Machine Learning: Class 2 | [
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Welcome back, folks! Its time to unravel the mystery of Machine Learning. This is the
Ilyas Habeeb
https://towardsdatascience.com/my-journey-into-machine-learning-class-3-c8139736f550 | My Journey into Machine Learning: Class 3 | [
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Hello, everyone! Thank you for taking the Machine Learning voyage with me! This is the
Ilyas Habeeb
https://towardsdatascience.com/my-journey-into-machine-learning-class-4-eb0f681cec65 | My Journey into Machine Learning: Class 4 | [
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A young brother in my church organized a capacity building class on Data analysis using
Daniel Ajisafe
https://towardsdatascience.com/my-vision-and-mission-as-a-data-scientist-670d2406639 | MY VISION AND MISSION AS A DATA SCIENTIST | [
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Bayes theorem finds many uses in the probability theory and statistics. Theres a micro chance that you
Prashant Gupta
https://towardsdatascience.com/naive-bayes-in-machine-learning-f49cc8f831b4 | Naive Bayes in Machine Learning | [
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Anybody who have a glimpse of machine learning does know about nearest neighbour classifier as it is one of
Abhiue Anand
https://towardsdatascience.com/nearest-neighbour-classifier-4ad15516873 | Nearest Neighbour Classifier | [
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Learn the Machine Learning Magic behind
Dave Smith
https://towardsdatascience.com/netflix-and-chill-building-a-recommendation-system-in-excel-c69b33c914f4 | Netflix and Chill: Building a Recommendation System in Excel | [
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Translation from English to French using
Ravindra Kompella
https://towardsdatascience.com/neural-machine-translation-using-seq2seq-with-keras-c23540453c74 | Neural Machine TranslationUsing seq2seq with Keras | [
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MT
Susan Li
https://towardsdatascience.com/neural-machine-translation-with-python-c2f0a34f7dd | Neural Machine Translation with Python | [
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We are experiencing a Cambrian explosion of neural network architectures. Each new design is scored with a benchmarkhow well does it recognize cats? can it play Atari games? does it detect stop signs? Researchers compare the performance of their neural network to other
Anthony Repetto
https://towardsdatascience.com/neu... | Neural Network Benchmarks | [
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What happens when a knowledge-based black box crashes a car or misdiagnoses a patient? Explanation methods give us insight
Brendan Whitaker
https://towardsdatascience.com/neural-network-explanation-methods-solutions-to-the-uber-incident-in-arizona-7660fc6759c2 | Layer-wise relevance propagation and other neural network explanation methods. | [
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We are going to build a neural network from scratch in Python without the use of a library. The iris data is
Rohan Joseph
https://towardsdatascience.com/neural-network-on-iris-data-4e99601a42c8 | Neural network on iris data | [
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A comparison study based on TensorFlow
Vadim Smolyakov
https://towardsdatascience.com/neural-network-optimization-algorithms-1a44c282f61d | Neural Network Optimization Algorithms | [
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A Dying Industry
Peter Akioyamen
https://towardsdatascience.com/neural-networks-deep-learning-the-revival-of-hft-2bc2c271fba2 | Neural Networks & Deep LearningThe Revival of HFT? | [
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The problem that we(me and my friend) have tackled is Bird detection and segmentation from images, this is a vital
Tushar Gupta
https://towardsdatascience.com/new-segmentation-paradigm-fc34b6dab993 | New Segmentation Paradigm | [
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Taking baby steps when starting DL
Arkar Min Aung
https://towardsdatascience.com/newbies-guide-to-deep-learning-6bf601c5a98e | Newbies guide to Deep Learning | [
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Motto: Start strong. Establish small victories. Win each quarter.
Phillip Hale
https://towardsdatascience.com/nfl-which-quarters-correlate-most-with-winning-87f23024c44a | NFLDoes winning in the first quarter really matter in the NFL? | [
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1 billion tests performed a year and not a data scientist in sight
Ross Burton
https://towardsdatascience.com/nhs-laboratories-need-data-science-c93f7983302c | NHS Laboratories need Data Science | [
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What if radiology artificial intelligence was used
Hugh Harvey
https://towardsdatascience.com/nightmare-on-ml-street-the-dark-potential-of-ai-in-radiology-71074e70da91 | Nightmare on ML Street: the dark potential of AI in radiology | [
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Natural Language Generation is a very important area to be explored in our time. It
AMR
https://towardsdatascience.com/nlg-for-fun-automated-headlines-generator-6d0459f9588f | NLG for FunAutomated Headlines Generator | [
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Doing cool things with data!
Priya Dwivedi
https://towardsdatascience.com/nlp-building-a-question-answering-model-ed0529a68c54 | NLPBuilding a Question Answering model | [
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Learn almost everything about Neural Networks!
Suryansh S.
https://towardsdatascience.com/nns-aynk-c34efe37f15a | Neural Networks: All YOU Need to Know | [
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Start building your own machine learning experiments fast and without breaking a sweat with Microsoft Azure Notebooks and a Microsoft account.
John Paul Ada
https://towardsdatascience.com/no-hassle-machine-learning-experiments-with-azure-notebooks-e1a22e8782c3 | No-Hassle Machine Learning Experiments with Azure Notebooks | [
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Today I am going to discuss a recent paper which I read and presented to some of my friends. I
Divyansh Jha
https://towardsdatascience.com/not-just-another-gan-paper-sagan-96e649f01a6b | Not just another GAN paperSAGAN | [
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A beginners guide to Reinforcement Learning
Partha Pratim Neog
https://towardsdatascience.com/not-so-deep-reinforcement-learning-for-dummies-part-1-c22416a55535 | Not-So-Deep Reinforcement Learning for dummies Part 1 | [
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Markov Decision ProcessesA beginners guide
Partha Pratim Neog
https://towardsdatascience.com/not-so-deep-reinforcement-learning-for-dummies-part-2-854216d1fe0d | Not-So-Deep Reinforcement Learning for dummiesPart 2 | [
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paper
Nikhil Balaji
https://towardsdatascience.com/notes-on-matrix-calculus-for-deep-learning-b9899effa7cf | Notes on Matrix Calculus for Deep Learning | [
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Deep learning is widely used nowadays. There are a lot of interesting applications of neural networks in computer vision tasks. This tutorial will introduce you to how you can easily build number plate detection system
Supervise.ly
https://towardsdatascience.com/number-plate-detection-with-supervisely-and-tensorflow-pa... | Number plate detection with Supervisely and Tensorflow (Part 1) | [
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Moses Olafenwa
https://towardsdatascience.com/object-detection-with-10-lines-of-code-d6cb4d86f606 | Object Detection with 10 lines of code | [
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When objects are of similar size and shape, like these rainbow donuts, they can be
Mike Alatortsev
https://towardsdatascience.com/object-detection-without-machine-learning-aed3c5b668f3 | Object detection without Machine Learning | [
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The task of object localization is to predict the object in an image as well as its boundaries. The difference between object localization and object detection is subtle. Simply, object localization aims to locate the main (or most visible) object in an image while object
Hao Gao
https://towardsdatascience.com/object-l... | Object Localization in Overfeat | [
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Breaking down the impact they provide and why the next generation
Conor Dewey
https://towardsdatascience.com/ode-to-the-type-a-data-scientist-78d11456019 | An Ode to the Type A Data Scientist | [
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This article summarizes a novel technique for a very complex task in NLP known as noun compound classification.
elvis
https://towardsdatascience.com/olive-oil-is-made-of-olives-baby-oil-is-made-for-babies-paper-summary-265bea33605b | Olive Oil is Made of Olives, Baby Oil is Made for Babies [Paper Summary] | [
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68 years ago, Alan Turing proposed the question Can Machines Think in his seminal paper titled
John Olafenwa
https://towardsdatascience.com/on-the-subject-of-thinking-machines-c3ba65a7105 | On The Subject of Thinking Machines | [
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I cant decide if that is a scary thought. I feel excitement and trepidation. Westworld made
Avinash Royyuru
https://towardsdatascience.com/one-of-us-is-going-to-build-westworld-bab187275ec8 | One of us is going to build Westworld | [
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A new report from the USAs National Academies of Science, Engineering and Medicine lays out the promise of open science and the challenges ahead
Jon Brock
https://towardsdatascience.com/open-science-by-design-30ec5abd4efa | Open science by design | [
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Operating a data science team is not something that can just be learned by watching
SeattleDataGuy
https://towardsdatascience.com/operating-a-data-science-team-is-not-something-that-can-just-be-learned-by-watching-lectures-and-fef6ed0f714a | Practically Managing A Data Science Team | [
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I am motivated by the vision of how Manufacturing Operations and Procurement industry will evolve in the year 2022
Gaurav Sharma
https://towardsdatascience.com/operations-in-year-2022-57c5f8d92bd5 | Operations in Year 2022 | [
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Note: this post is based on talks I recently gave at Facebook Developer Circles and
Boyan Angelov
https://towardsdatascience.com/optimal-tooling-for-machine-learning-and-ai-e43495db59da | Optimal Tooling for Machine Learning and AI | [
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With the rise of plenty of deep learning frameworks, its becoming easier to train deep
Aditya Ananthram
https://towardsdatascience.com/optimizers-be-deeps-appetizers-511f3706aa67 | Optimizers be TensorFlows Appetizers | [
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Working with large data sets on a simple laptop.
Kevin Arvai
https://towardsdatascience.com/out-of-core-genomics-8aa5ef487d1e | Out of Core Genomics | [
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During a recent project I was working on a clustering problem with data collected from
Eryk Lewinson
https://towardsdatascience.com/outlier-detection-with-isolation-forest-3d190448d45e | Outlier Detection with Isolation Forest | [
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In supervised machine learning, models are trained on a subset of data aka training data. The goal is to compute the target of each training example from the training data.
Anuja Nagpal
https://towardsdatascience.com/over-fitting-and-regularization-64d16100f45c | Over-fitting and Regularization | [
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While working on natural language models for search engines, I have frequently
Sanket Gupta
https://towardsdatascience.com/overview-of-text-similarity-metrics-3397c4601f50 | Overview of Text Similarity Metrics in Python | [
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A look at the P2P lending landscape in the US with pandas
Finn Qiao
https://towardsdatascience.com/p2p-lending-for-home-flippers-and-minorities-ed9aba6da4cb | P2P Lending for Home Flippers and Minorities | [
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Checking how similar two sequences are using Python tools
Vijini Mallawaarachchi
https://towardsdatascience.com/pairwise-sequence-alignment-using-biopython-d1a9d0ba861f | Pairwise Sequence Alignment using Biopython | [
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This is a paper in a Seminal Papers in ML series by MIT Machine Intelligence
Ali Shan Zartash
https://towardsdatascience.com/paper-summary-optimal-dnn-primitive-selection-with-partitioned-boolean-quadratic-programming-84d8ca4cdbfc | Faster Deep Learning: Optimal DNN Primitives | [
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What to do if a genetic algorithm is not sufficient?
Ivan
https://towardsdatascience.com/parallel-and-distributed-genetic-algorithms-1ed2e76866e3 | Parallel and distributed genetic algorithms | [
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In this tutorial I will explain about the relation between PCA and an Autoencoder (AE). I assume that you have a basic grasp
Ori Cohen
https://towardsdatascience.com/pca-vs-autoencoders-1ba08362f450 | PCA vs Autoencoders | [
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Every year a lot of companies hire a number of employees. The companies invest time
Natasha Sharma
https://towardsdatascience.com/people-analytics-with-attrition-predictions-12adcce9573f | People Analytics with Attrition Predictions | [
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Phishing is a form of fraud in which the attacker tries to learn sensitive information such as login
Ebubekir B ber
https://towardsdatascience.com/phishing-domain-detection-with-ml-5be9c99293e5 | Phishing URL Detection with ML | [
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If Software 2.0 is Deep Learning, Photoshop 2.0 is GAN
Pranoy Radhakrishnan
https://towardsdatascience.com/photoshop-2-0-a49990e483 | Photoshop 2.0 | [
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The science behind personalized
James Le
https://towardsdatascience.com/pinterests-visual-lens-how-computer-vision-explores-your-taste-5470f87502ad | Pinterests Visual Lens: How computer vision explores your taste | [
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... |
Machine learning is awesome, except when it forces you to do advanced math. The tools for machine learning
Yufeng G
https://towardsdatascience.com/plain-and-simple-estimators-d8d3f4c185c1 | Plain and Simple Estimators | [
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In my previous articles, we discussed the data characteristics and common issues
Krishna Kumar Tiwari
https://towardsdatascience.com/play-with-data-2a5db35b279c | Magic with Data | Titanic Survival Prediction | [
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#2 Research Paper Explained
SAGAR SHARMA
https://towardsdatascience.com/playing-atari-with-6-neurons-open-source-code-b94c764452ac | Playing ATARI with 6 Neurons | Open Source Code | [
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0.3805346190929413,
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-0.1177812740... |
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