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In this article, we will see the complete derivation of the Sigmoid function as used in Artificial
Arunava
https://towardsdatascience.com/derivative-of-the-sigmoid-function-536880cf918e | Derivative of the Sigmoid function | [
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Mixing, creating and searching
Norman Di Palo
https://towardsdatascience.com/des-ai-gn-augmenting-human-creativity-with-artificial-intelligence-bb6ff611fa2c | des.ai.gnAugmenting human creativity with artificial intelligence | [
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Design your engineering
Tirthajyoti Sarkar
https://towardsdatascience.com/design-your-engineering-experiment-plan-with-a-simple-python-command-35a6ba52fa35 | Design your engineering experiment plan with a simple Python command | [
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What Designing for Humans Reveals about the Mind
Sheldon J. Pacotti
https://towardsdatascience.com/designing-intelligence-c78f9959b3b8 | Designing Intelligence | [
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Get started with XGBoost quickly
Priansh Shah
https://towardsdatascience.com/detect-parkinsons-with-10-lines-of-code-intro-to-xgboost-51a4bf76b2e6 | Save Lives With 10 Lines of Code: Detecting Parkinsons with XGBoost | [
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Breast cancer is the most common invasive cancer in women, and the second main cause of cancer death in women, after lung cancer. In this article I will build a
Favio V zquez
https://towardsdatascience.com/detecting-breast-cancer-with-a-deep-learning-10a20ff229e7 | Detecting Breast Cancer with Deep Learning | [
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Maybe you were wondering how you can place funny objects on faces in real-time
Peter Skvarenina
https://towardsdatascience.com/detecting-facial-features-using-deep-learning-2e23c8660a7a | Detecting facial features using Deep Learning | [
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Pneumonia is an infection in one or both lungs. It can be caused by bacteria, viruses, or fungi. Bacterial pneumonia is the most common type in adults.Pneumonia causes inflammation in the air
Rajat
https://towardsdatascience.com/detecting-pneumonia-with-deep-learning-studio-a1bd39ef1923 | Detecting Pneumonia with Deep Learning Studio | [
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Developing 1d/2d data container and transformers for data analysis
Vitaly Davydov
https://towardsdatascience.com/developing-1d-2d-data-container-and-transformers-for-data-analysis-9790bfd75ac7 | [
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Last year, I hit the pause button in my life and moved, temporarily at the time, to Seattle. I entered the Galvanize Data Science
Stef Bernosky
https://towardsdatascience.com/dfl-dnf-dns-60969b9e995d | DFL > DNF > DNS? | [
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Google unveiled an AI that can make reservations
Artem Oppermann
https://towardsdatascience.com/did-google-duplex-beat-the-turing-test-yes-and-no-a2b87d1c9f58 | Did Google Duplex beat the Turing Test? Yes and No. | [
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My models say uh-uh.
Jason Peterson
https://towardsdatascience.com/did-melania-really-tweet-that-d8038e91e67f | Did Melania Really Tweet That? | [
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[WARNING: TOO EASY!]
Aerin Kim
https://towardsdatascience.com/difference-between-batch-gradient-descent-and-stochastic-gradient-descent-1187f1291aa1 | Difference between Batch Gradient Descent and Stochastic Gradient Descent | [
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Analysts who are used to the structured data which gives them perfect data will have frustration at the beginning
Sibel Akcekaya
https://towardsdatascience.com/digital-analytics-data-quality-and-web-analysts-e5f6cc709f4a | Digital Analytics Data Quality and Web Analysts | [
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Lets take a quick look at what digital economics is all about, and how it impacts both organizations and markets.
Lee Schlenker
https://towardsdatascience.com/digital-economics-825ea18cd1f4 | Digital Economics | [
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TWiML Talk 117
Sam Charrington
https://towardsdatascience.com/discovering-exoplanets-with-deep-learning-fcf8873391c9 | Discovering Exoplanets with Deep Learning | [
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How Artificial Intelligence and Machine
Prannoiy Chandran
https://towardsdatascience.com/disruption-in-retail-ai-machine-learning-big-data-7e9687f69b8f | Disruption in RetailAI, Machine Learning & Big Data | [
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A few weeks ago in an article titled How much runway should you target between
Sebastian Quintero
https://towardsdatascience.com/dissecting-startup-failure-by-stage-34bb70354a36 | Dissecting startup failure rates by stage | [
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Determining NBA Potential
Abhijit Brahme
https://towardsdatascience.com/dissecting-the-nba-draft-part-2-79b6bd486a8d | Dissecting the NBA Draft: Part 2 | [
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I read an interesting embargoed article in JAMA. Initially I was just going to wait for the embargo to lift today at 11:00 a.m. and share across a few platforms but I had a few days to think about the findings. With time to kill I read a few of the citations.
Bonny P McClain
https://towardsdatascience.com/distorting-da... | Distorting data with race | [
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If my product succeeds will this eventual-consistency
Pritam Roy
https://towardsdatascience.com/distributed-transactions-and-why-you-should-care-116b6da8d72 | Distributed transactions and why you should care | [
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Inspired by the great work of Akshay Bahadur in this article you will see some projects applying Computer Vision and Deep Learning, with implementations and details so you can
Favio V zquez
https://towardsdatascience.com/diy-deep-learning-projects-c2e0fac3274f | DIY Deep Learning Projects | [
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As careers and lifestyles develop, we are becoming more and more dependent on software development. A few decades
Syed Sadat Nazrul
https://towardsdatascience.com/diy-pokedex-with-python-be32e5e3006e | DIY Pokedex with Python! | [
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AI is the goal for many enterprises. But, an organization needs machine learning, in order to do AI. And, machine
Rob Thomas
https://towardsdatascience.com/do-data-science-faster-fe27294fd417 | Do Data Science Faster | [
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A convolutional neural network typically has multiple convolutional layers (hence, the
Naoki Shibuya
https://towardsdatascience.com/do-filters-dream-of-convolutional-cats-5cd5d1f7e2ff | Do Filters Dream of Convolutional Cats? | [
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Music is something that is part of footballs culture. Official FIFA and local
Bo Plantinga
https://towardsdatascience.com/do-match-days-boost-the-fifa-world-cup-soundtrack-d75d7ef785c1 | Do match-days boost the FIFA World Cup song? | [
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Dont do something interesting with data, AI, and MLdo something
Chris Butler
https://towardsdatascience.com/do-something-interesting-50a3876a1af3 | [
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Are data labelers a new trend?
Priscilla Ara jo
https://towardsdatascience.com/do-you-know-what-does-a-data-labeler-do-98561cb0029 | Do You Know What Does a Data Labeler Do? | [
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Docker is a tool that simplifies the installation process for software engineers. Coming from a statistics background
Sachin Abeywardana
https://towardsdatascience.com/docker-for-data-science-4901f35d7cf9 | Docker for Data Science | [
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If you choose a way of Data Science you should know a lot of tools like python, NumPy, Pandas, Matplotlib, SciPy
Evheniy Bystrov
https://towardsdatascience.com/docker-for-data-science-9c0ce73e8263 | Docker for Data Science | [
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Heres a few ways you can ensure it does
Tricia Aanderud
https://towardsdatascience.com/does-your-data-visualization-have-a-takeaway-a58f0650f243 | Does Your Data Visualization have a Takeaway? | [
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End-to-end example of how to build a deep learning model
Kirill Panarin
https://towardsdatascience.com/dog-breed-classification-hands-on-approach-b5e4f88c333e | Dog Breed Classification: hands-on approach | [
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Exploratory Data Analysis, or EDA, makes up a good portion of a data scientists work. In fact, according to the 2017 OReillys data science survey, basic EDA is the data scientists most common
Chaim Gluck
https://towardsdatascience.com/doing-eda-on-a-classification-project-pandas-crosstab-will-change-your-life-c61c1cb2c... | Doing EDA on a classification project? pandas.crosstab will change your life. | [
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Mathematical Scaling in Canadian Fast Food Service
Anders Ohrn
https://towardsdatascience.com/donuts-coffee-meet-the-city-economy-12a540faf83b | Donuts & Coffee Meet The City Economy | [
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This article is about a side project by Mary Kate MacPherson. We like to do side projects
Daniel Shapiro, PhD
https://towardsdatascience.com/drawing-anime-girls-with-deep-learning-4fa6523eb4d4 | Drawing Anime Girls With Deep Learning | [
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Something fundamental changed between last
Kiki Jewell
https://towardsdatascience.com/drinkbots-new-technologies-and-ageism-in-silicon-valley-26fa18172fb8 | DrinkBots, New Technologies, and Ageism in Silicon Valley | [
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And how to fight occasional burnouts
Oleksii Kharkovyna
https://towardsdatascience.com/ds-is-bs-why-data-scientists-are-discouraged-in-their-field-baea605f5fe | DS is BS: why data scientists are discouraged in their field | [
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A new way of deep learning Tensorflow 1.7.
Keshav Aggarwal
https://towardsdatascience.com/eager-execution-tensorflow-8042128ca7be | A brief guide to Tensorflow Eager Execution | [
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Among all technological advances that the world will continue to witness, few outstrip, in terms of benefits for humanity, the
Guy Perelmuter
https://towardsdatascience.com/editing-fate-cdc50429757c | Editing fate | [
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The biggest impediment to adoption of AI is lack of knowledge. What do enterprise companies and other ecosystem players need to learn?
Mike Mitchell
https://towardsdatascience.com/educating-the-enterprise-on-ai-f1d206809910 | Educating the Enterprise on AI | [
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and how it improves your data science code.
Kemal Tugrul
https://towardsdatascience.com/effective-naming-in-data-science-ea847c04f51b | The Effect of Naming in Data Science Code | [
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Beyond the bound
Kyle Li
https://towardsdatascience.com/efficient-frontier-optimize-portfolio-with-scipy-57456428323e | Portfolio Optimization for Minimum Risk with ScipyEfficient Frontier Explained | [
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Brief Overview of Salesforces Einstein Platform Services
Max Frolov
https://towardsdatascience.com/einstein-platform-fuel-for-ai-enabled-world-508fbbdb82a5 | Einstein Platform: Fuel for AI-enabled World | [
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Clustering is the process of taking a pile of unsorted stuff (your dataset) and
Daniel Shapiro, PhD
https://towardsdatascience.com/elbow-clustering-for-artificial-intelligence-be9c641d9cf8 | Elbow Clustering for Artificial Intelligence | [
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My favorite part about my General Assembly experience thus far has been the web scraping
Andres Gonzalez
https://towardsdatascience.com/elements-of-a-data-scientists-salary-1dc547f6d888 | Elements of a Data Scientists Salary | [
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The newly released Tensorflow hub provides an easy interface to use existing machine learning models for transfer learning. Sometimes, however, its nice to fire up Keras and quickly prototype a model. With a few fixes, its easy to integrate a
Jacob Zweig
https://towardsdatascience.com/elmo-embeddings-in-keras-with-tens... | Elmo Embeddings in Keras with TensorFlow hub | [
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An introduction to unsupervised learning of word embeddings from
Brendan Whitaker
https://towardsdatascience.com/emnlp-what-is-glove-part-i-3b6ce6a7f970 | [EMNLP] What is GloVe? Part I | [
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An introduction to unsupervised learning of word embeddings from co-occurrence matrices.
Brendan Whitaker
https://towardsdatascience.com/emnlp-what-is-glove-part-ii-9e5ad227ee0 | [EMNLP] What is GloVe? Part II | [
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An introduction to unsupervised learning of word embeddings from
Brendan Whitaker
https://towardsdatascience.com/emnlp-what-is-glove-part-iii-c6090bed114 | [EMNLP] What is GloVe? Part III | [
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An introduction to unsupervised learning of word embeddings from
Brendan Whitaker
https://towardsdatascience.com/emnlp-what-is-glove-part-iv-e605a4c407c8 | [EMNLP] What is GloVe? Part IV | [
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An introduction to unsupervised learning of word embeddings from co-occurrence matrices.
Brendan Whitaker
https://towardsdatascience.com/emnlp-what-is-glove-part-v-fa888272c290 | [EMNLP] What is GloVe? Part V | [
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Emoji usage has become a new form of social communication, which is important because it can
elvis
https://towardsdatascience.com/emoji-prediction-using-time-embeddings-de124d8c8c6e | Emoji Prediction using Time Embeddings | [
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Interactive Text Mining and Information Retrieval
Marco Brambilla
https://towardsdatascience.com/enhancing-human-perception-f5e6c82baf44 | Enhancing Human Perception with ML, AI, IR and NLP | [
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Use multiple neural nets to obtain better predictive performance
Max Lawnboy
https://towardsdatascience.com/ensembling-convnets-using-keras-237d429157eb | Ensembling ConvNets using Keras | [
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Know your code
SAGAR SHARMA
https://towardsdatascience.com/epoch-vs-iterations-vs-batch-size-4dfb9c7ce9c9 | Epoch vs Batch Size vs Iterations | [
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Strategies to follow when fixing errors in your algorithm
Kritika Jalan
https://towardsdatascience.com/error-analysis-to-your-rescue-773b401380ef | Error Analysis to Your Rescue! | [
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Job of a Footballer and a Data
Prasad Patil
https://towardsdatascience.com/estimate-the-favorite-scraping-tweets-using-python-863303384e29 | Finding the favorite team in 2018 FIFA World Cup through scraping Tweets | [
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In this episode of Cloud AI Adventures, learn how to train on increasingly complex
Yufeng G
https://towardsdatascience.com/estimators-revisited-deep-neural-networks-311f38fe1986 | Estimators revisited: Deep Neural Networks | [
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Introduction and glimpse at practice
Anuradha Wickramarachchi
https://towardsdatascience.com/event-driven-architecture-pattern-b54fc50276cd | Event Driven Architecture Pattern | [
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How AI works. What you can do with it. And how to get started.
Markus Schmitt
https://towardsdatascience.com/everything-a-ceo-needs-to-know-about-ai-35048caea84c | Everything A CEO Needs To Know About AI | [
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A Data Science Study on Influence of
Marco Brambilla
https://towardsdatascience.com/evolution-of-attention-towards-scientists-and-research-topics-based-on-awards-a2453ebb574 | Evolution of Attention towards Scientists and Research Topics | [
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Since the release of Dreamcast and the modem adapter, game developers have been able to
Ben Weber
https://towardsdatascience.com/evolution-of-game-analytics-platforms-4b9efcb4a093 | The Platform Evolution of Game Analytics | [
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Due to its potential to improve our lives with abundant possibilities
Ved Vasu Sharma
https://towardsdatascience.com/evolution-of-kernel-the-backbone-of-squadai-7c605ec64b28 | Evolution of Kernel: The backbone of SquadAI | [
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expectations management
Peadar Coyle
https://towardsdatascience.com/expectations-management-or-how-i-learned-to-not-be-scared-of-business-speak-8f5b9b8e3d22 | Expectations management or how I learned to not be scared of business speak | [
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Caveat: Some prior knowledge of CNNs is assumed for this post
Sahil Singla
https://towardsdatascience.com/experiments-with-a-new-kind-of-convolution-dfe603262e4c | Experiments with a new kind of convolution | [
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Authors:
Mouhamadou-Lamine Diop
https://towardsdatascience.com/explainable-ai-the-data-scientists-new-challenge-f7cac935a5b4 | Explainable AI: The data scientists new challenge | [
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In my job, I help ordinary people understand complex data. Every once in a while someone is
Jasper McChesney
https://towardsdatascience.com/explaining-paradoxical-trends-in-data-25ce4b6eec40 | Explaining Paradoxical Trends in Data | [
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This blog post is dedicated to the analysis using data visualization of the Pokemon dataset. The first part will be
Akshaj Verma
https://towardsdatascience.com/exploratory-analysis-of-pokemons-using-r-8600229346fb | GgPlot Em All | Pokemon | [
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As I was contemplating what could be the maiden topic I should
Prasad Patil
https://towardsdatascience.com/exploratory-data-analysis-8fc1cb20fd15 | What is Exploratory Data Analysis? | [
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Extracting meaning from unstructured data is a difficult thing to do. Sometimes, if youre lucky, there are
Ben Rudolph
https://towardsdatascience.com/exploring-comments-on-reddit-c10ad36dbb8f | Exploring Comments on Reddit | [
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Facial Recognition systems have become main stream technologies. Recently, both Apple and
Saurav Chakravorty
https://towardsdatascience.com/facial-recognition-adversarial-attack-analytics-applied-on-wordpress-com-32b7622b8fb1 | Facial Recognition & Adversarial Attack | [
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While modern self-service is working for consumers, IT self-service portals are stuck on the launch pad. However, IT delivering out of this world service to its customers is a mission thats far too important to abort. Instead we
Rob Young
https://towardsdatascience.com/failure-to-launch-it-we-have-a-self-service-proble... | Failure to launch: IT, we have a (self-service) problem! | [
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95% of statistics are made up.
Anthony Carminati
https://towardsdatascience.com/fake-news-and-the-responsibility-of-data-scientists-b74d176d7bd1 | Fake News and the Responsibility of Data Scientists | [
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This lesson is part of the lessons offered by DeepSchool.io. We use Deep Learning (Recurrent Neural
Sachin Abeywardana
https://towardsdatascience.com/fake-news-classifier-e061b339ad6c | Fake News Classifier (using LSTMs) | [
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Experimenting with software development pipelines in machine
Christian Melchiorre
https://towardsdatascience.com/fantastic-models-and-how-to-train-them-experimenting-with-software-development-pipelines-in-7051b9d930f7 | Fantastic Models and how to Train Them | [
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In this post, I will demonstrate how to use google colab for fastai.
Manikanta Yadunanda
https://towardsdatascience.com/fast-ai-lesson-1-on-google-colab-free-gpu-d2af89f53604 | Fast.ai Lesson 1 on Google Colab (Free GPU) | [
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fast.ai is an online platform to learn Deep Learning (DL). It has 14 lectures
Srinandaka Yashaswi
https://towardsdatascience.com/fast-ai-v2-lesson1-synopsis-tl-dr-4985bba9eea2 | What youll learn from fast.ai (V2) Lesson1 | [
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A quick 5-part tutorial on how deep
Gal Yona
https://towardsdatascience.com/fast-near-duplicate-image-search-using-locality-sensitive-hashing-d4c16058efcb | Fast Near-Duplicate Image Search using Locality Sensitive Hashing | [
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Getting to solving actual problems
Said Aspen
https://towardsdatascience.com/fast-track-to-the-other-side-of-the-ai-hype-collapse-d54bb1393091 | Fast track to the other side of the AI hype collapse | [
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Where we look at how one of the best performing embeddings library is
Nishan Subedi
https://towardsdatascience.com/fasttext-under-the-hood-11efc57b2b3 | FastText: Under the Hood | [
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I had asked on LinkedIn recently about everyones favorite MOOCs in data science. This post started
Kristen Kehrer
https://towardsdatascience.com/favorite-moocs-for-data-scientists-10b16a950e36 | Favorite MOOCs for Data Scientists | [
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Arguably, the features that enter a supervised learning model are more important than the model
Jan Krepl
https://towardsdatascience.com/feature-transformers-hidden-gems-917bc1237f90 | Feature Transformers: Hidden Gems | [
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FEDERATED MACHINE LEARNING
vibhor nigam
https://towardsdatascience.com/federated-machine-learning-c99dd5dec201 | FEDERATED MACHINE LEARNING | [
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Hollywood has made many big promises about artificial intelligence(AI) in the past: how it will destroy us, how
Zack Akil
https://towardsdatascience.com/fibre-optic-ai-for-my-apartment-wall-99f2efd4c507 | Fibre optic neural network | [
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WordCloud using less than 40 lines of R Code
Kritika Jalan
https://towardsdatascience.com/find-out-what-celebrities-tweet-about-the-most-6f498d89266b | Find Out What Celebrities Tweet About the Most | [
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In this article, we will explain how autoencoders can be used for finding similar
Anson Wong
https://towardsdatascience.com/find-similar-images-using-autoencoders-315f374029ea | Finding Similar Images using Autoencoders | [
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You may have seen my previous post about what DataScienceGO 2018 is, where its happening
Kirill Eremenko
https://towardsdatascience.com/finding-big-value-in-small-conferences-d5178295d773 | Finding Big Value in Small Conferences | [
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Today I want to understand the distribution of the characteristics of TED talksare
Hannah Yan Han
https://towardsdatascience.com/finding-characteristics-of-ted-talks-911879560146 | Finding the Characteristics of TED talks | [
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Hello, in this project I will attempt to find lane lines from a dash cam video feed
Percy Jaiswal
https://towardsdatascience.com/finding-driving-lane-line-live-with-opencv-f17c266f15db | Finding Driving Lane Line live with OpenCV | [
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mining ingredients with association rules
Hannah Yan Han
https://towardsdatascience.com/finding-the-pattern-of-food-a462b3ce5910 | Finding the pattern of food | [
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When the President tweets, how do we know who is really behind the
J. Allen-Robertson
https://towardsdatascience.com/finding-trump-with-neural-networks-4419468e0624 | Finding Trump with Neural Networks | [
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Its easy to understand that many machine learning problems benefit from either precision
Kevin Arvai
https://towardsdatascience.com/fine-tuning-a-classifier-in-scikit-learn-66e048c21e65 | Fine tuning a classifier in scikit-learn | [
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This weekend students learnt about the fundamentals that underpin many of the machine
Cambridge Spark
https://towardsdatascience.com/first-weekend-at-applied-data-science-2017-23c86415c1b8 | First weekend at Applied Data Science 2017 | [
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Back with another weird idea which is, as always
JC Testud
https://towardsdatascience.com/food-ingredient-reverse-engineering-through-gradient-descent-2a8d3880dd81 | Food Ingredient Reverse-Engineering Through Gradient Descent | [
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General Assembly has ended. Projects were presented. Hugs were given. A few months later, Ive been selected to give an
Chris Kim
https://towardsdatascience.com/forecasting-the-future-272365dcb75d | Forecasting the Future | [
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On a trip to London last week, we took a trip down Brick lane to see the
Daryl Feehely
https://towardsdatascience.com/found-this-week-68-db5f4ffaf530 | Found This Week #68 | [
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Building a user-friendly app to analyze big data in real time (that is, keeping response times below 60 seconds) is a challenge. In the big data world, youre either doing batch analytics where nobody really cares about
Tom Grek
https://towardsdatascience.com/four-fails-and-a-win-at-a-big-data-stack-for-realtime-analyti... | Four fails and a win at a big data stack for realtime analytics | [
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Fraud Analytics
Chief Data Scientist
https://towardsdatascience.com/fraud-analytics-technology-can-make-fraud-detection-affordable-b1201ad1e2b4 | Fraud analytics: Technology can make fraud detection affordable | [
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Visualizing and decoding
Norman Di Palo
https://towardsdatascience.com/from-brain-waves-to-arm-movements-with-deep-learning-an-introduction-3c2a8b535ece | From brain waves to robot movements with deep learning: an introduction. | [
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How does someone transition from being a Data Analyst to Data Scientist?
Ben Stanbury
https://towardsdatascience.com/from-data-analyst-to-data-scientist-f67a724ea265 | From Data Analyst to Data Scientist | [
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0.1098024770617485,
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0.4342762231826782,
0.11480088531970978,
-0.05387207120656... |
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