A “Data Science for Good“ Machine Learning Project Walk-Through in Python: Part One by @koehrsen_will via @TDataScience https://t.co/5PzRvK7tRA #python #datascience #machinelearning pic.twitter.com/DLUt4zeNxJ
— Python Weekly (@PythonWeekly) August 29, 2018
📊 always cool to see a chart's evolution…
— Mara Averick (@dataandme) August 29, 2018
"How to Make Better-Looking, More Readable Charts in R" 👨💻 @flowingdata https://t.co/I6Fe4RSz5c #rstats #dataviz pic.twitter.com/CMC5YMhUSx
This is still one of the most impressive Deep Learning demos of 2018 - huge opportunity for new open-source Web Development tools based on merely 200 lines of Keras code. Anyone building any?
— Trask (@iamtrask) August 29, 2018
(Huge #100DaysOfMLCode opportunity, IMO)https://t.co/5hrIyWlIlq
This is the most extensive list of "From Scratch Machine Learning" I've ever seen - this is a golden resource if your learn like I do (by building things from scratch).https://t.co/LcoPAQBULv
— Trask (@iamtrask) August 28, 2018
🌟 guide: "Laying out multiple plots on a page" by @tpabhttps://t.co/GPgRPau8LN #rstats #dataviz #ggplot2 pic.twitter.com/oBxiaD6M2u
— Mara Averick (@dataandme) August 28, 2018
The ultimate peer-to-peer guide on getting started with our #machinelearning competitions, written by Kaggler, @koehrsen_will. https://t.co/6R4INgkQLd
— Kaggle (@kaggle) August 24, 2018
"End to-end goal-oriented question answering systems" #KDD2018 Tutorial [SLIDES] https://t.co/Exn9sloCho - A lot of good #nlp stuff in these 200 slides
— Xavier 🎗🤖🏃 (@xamat) August 22, 2018
💪 tidy up your corrrr…
— Mara Averick (@dataandme) August 21, 2018
"Exploring correlations in R with corrr" 👨⚕️ @drsimonj https://t.co/5slkxW582M #rstats pic.twitter.com/dJQ1nxiER4
“Building a text classification model with TensorFlow Hub and Estimators” by TensorFlow https://t.co/ZgCYg2fV95 #deeplearning #machinelearning #ml #ai #neuralnetworks #tensorflow
— TensorFlow Best Practices (@TFBestPractices) August 19, 2018
Great intro to the rsample 📦 last night! Thanks @frannystats for the slow & easy walk-through and even some live coding 😮https://t.co/gL9JqqVmdO @RLadiesSF pic.twitter.com/GJfRv2Bd6P
— Irene Steves (@i_steves) August 16, 2018
Text classification with a small dataset? TF Hub to the rescue!
— TensorFlow (@TensorFlow) August 15, 2018
Learn how to use TF Hub’s pre-trained word embeddings in this tutorial by @SRobTweets ↓ https://t.co/7ecjca9VVL
Extensive example using Prophet to forecast time series (in this case, item-level demand forecasting, which has complex seasonal and holiday effects) https://t.co/E4hV9UL6UM
— Ben Hamner (@benhamner) August 14, 2018
