corpus.blog
41554 blogs · [ { "id": "01a0875b-1678-7056-aa35-eb01388ee6f4", "title": "Small team planning", "url": "https://bytepawn.com/small-team-planning.html", "published_at": "2020-01-09T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0138ea2679", "title": "Personal goaling", "url": "https://bytepawn.com/personal-goaling.html", "published_at": "2019-12-21T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0138ee5560", "title": "Pytorch in 2019", "url": "https://bytepawn.com/pytorch-in-2019.html", "published_at": "2019-12-11T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0139af848e", "title": "Warren Buffett style fundamental metrics of long-term company performance", "url": "https://bytepawn.com/warren-buffett-style-fundamental-metrics-of-long-term-company-performance.html", "published_at": "2019-12-01T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013a0d4a87", "title": "Calibration curves for delivery prediction with Scikit-Learn", "url": "https://bytepawn.com/calibration-curves-for-delivery-prediction-with-scikit-learn.html", "published_at": "2019-11-20T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013a211023", "title": "Using simulated self-play to solve all OpenAI Gym classic control problems with Pytorch", "url": "https://bytepawn.com/using-simulated-self-play-to-solve-all-openai-gym-classic-control-problems-with-pytorch.html", "published_at": "2019-11-13T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013a59fdd3", "title": "Applying policy gradient to OpenAI Gym classic control problems with Pytorch", "url": "https://bytepawn.com/solving-openai-gym-classic-control-problems-with-pytorch.html", "published_at": "2019-11-11T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013aef49af", "title": "Machine Learning at Fetchr", "url": "https://bytepawn.com/machine-learning-at-fetchr.html", "published_at": "2019-10-28T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013af079a2", "title": "Solving the CartPole Reinforcement Learning problem with Pytorch", "url": "https://bytepawn.com/solving-the-cartpole-reinforcement-learning-problem-with-pytorch.html", "published_at": "2019-10-21T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013b216c9e", "title": "Metrics Atlas", "url": "https://bytepawn.com/metrics-atlas.html", "published_at": "2019-08-28T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013c02112f", "title": "Playing Go with supervised learning in Pytorch", "url": "https://bytepawn.com/playing-go-with-supervised-learning-in-pytorch.html", "published_at": "2019-08-24T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013c06d1f6", "title": "Arabic name classification with Scikit-Learn and Pytorch", "url": "https://bytepawn.com/arabic-name-classification-with-scikit-learn-and-pytorch.html", "published_at": "2019-08-01T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013c2d036f", "title": "Exploring prior beliefs with MCMC", "url": "https://bytepawn.com/exploring-prior-beliefs-with-mcmc.html", "published_at": "2019-07-05T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013cb48faa", "title": "A/B tests: Moving Fast vs Being Sure", "url": "https://bytepawn.com/ab-tests-moving-fast-vs-being-sure.html", "published_at": "2019-06-30T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013d5f2bad", "title": "Food deliveries, Bayes and Computational Statistics", "url": "https://bytepawn.com/food-deliveries-bayes-and-computational-statistics.html", "published_at": "2019-06-21T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013e31f0a2", "title": "The Collatz conjecture", "url": "https://bytepawn.com/the-collatz-conjecture.html", "published_at": "2019-06-01T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013e8651e5", "title": "MNIST pixel attacks with Pytorch", "url": "https://bytepawn.com/mnist-pixel-attacks-with-pytorch.html", "published_at": "2019-05-31T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb013f26e9f4", "title": "Solving CIFAR-10 with Pytorch and SKL", "url": "https://bytepawn.com/solving-cifar-10-with-pytorch-and-skl.html", "published_at": "2019-05-13T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01401a026f", "title": "Solving MNIST with Pytorch and SKL", "url": "https://bytepawn.com/solving-mnist-with-pytorch-and-skl.html", "published_at": "2019-05-01T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0140ac1caf", "title": "SVM with Pytorch", "url": "https://bytepawn.com/svm-with-pytorch.html", "published_at": "2019-04-15T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014143ae8f", "title": "Hacker News Embeddings with PyTorch", "url": "https://bytepawn.com/hacker-news-embeddings-with-pytorch.html", "published_at": "2019-03-11T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01418d459c", "title": "rxe: literate and composable regular expressions", "url": "https://bytepawn.com/rxe-literate-and-composable-regular-expressions.html", "published_at": "2019-03-01T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01427884f0", "title": "PyTorch Basics: Solving the Ax=b matrix equation with gradient descent", "url": "https://bytepawn.com/pytorch-basics-solving-the-axb-matrix-equation-with-gradient-descent.html", "published_at": "2019-02-07T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0142936544", "title": "Automating a Call Center with Machine Learning", "url": "https://bytepawn.com/automating-a-call-center-with-machine-learning.html", "published_at": "2019-01-26T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014391810d", "title": "5 things that happened in Data Science in 2018", "url": "https://bytepawn.com/five-things-2018-data-science.html", "published_at": "2019-01-08T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014414ec0b", "title": "Warehouse locations with k-means", "url": "https://bytepawn.com/warehouse-locations-with-kmeans.html", "published_at": "2018-09-25T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01450fe48a", "title": "Growth Accounting and Backtraced Growth Accounting", "url": "https://bytepawn.com/backtraced-growth-accounting.html", "published_at": "2018-09-15T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0145fc48a2", "title": "Fetchr Data Science Infra at 1 year", "url": "https://bytepawn.com/fetchr-data-science-infra.html", "published_at": "2018-08-13T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01467ebc5b", "title": "What not to spend time on", "url": "https://bytepawn.com/what-not-to-spend-time-on.html", "published_at": "2018-07-22T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01468532df", "title": "Beat the averages", "url": "https://bytepawn.com/beat-the-averages.html", "published_at": "2018-07-06T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb0147787509", "title": "Building the Fetchr Data Science Infra on AWS with Presto and Airflow", "url": "https://bytepawn.com/fetchr-airflow.html", "published_at": "2018-03-13T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014855d5b2", "title": "Don’t build cockpits, become a coach", "url": "https://bytepawn.com/data-science-coaching.html", "published_at": "2016-11-08T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01489b463b", "title": "Beautiful A/B testing", "url": "https://bytepawn.com/beautiful-ab-testing.html", "published_at": "2016-06-04T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb01491eb3c2", "title": "Hack, HHVM and avoiding the Second-system effect", "url": "https://bytepawn.com/hack-hhvm-second-system-effect.html", "published_at": "2016-05-13T22:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014947269e", "title": "Einstein's amazing theory", "url": "https://bytepawn.com/einsteins-amazing-theory.html", "published_at": "2016-02-15T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014a3f6c66", "title": "Heisengames and the importance of patience in business", "url": "https://bytepawn.com/heisengames-business.html", "published_at": "2016-02-07T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014b0e37f6", "title": "Cloud9: Cloud coding that actually works", "url": "https://bytepawn.com/cloud9.html", "published_at": "2016-02-06T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014c067493", "title": "Luigi vs Airflow vs Pinball", "url": "https://bytepawn.com/luigi-airflow-pinball.html", "published_at": "2016-02-05T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014cd1d13d", "title": "Pinball review", "url": "https://bytepawn.com/pinball.html", "published_at": "2016-02-05T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014d6f6b54", "title": "How to make a blog like this", "url": "https://bytepawn.com/how-to-make-a-blog-like-this.html", "published_at": "2016-01-06T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014db0e209", "title": "Airflow review", "url": "https://bytepawn.com/airflow.html", "published_at": "2016-01-05T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014e8981f0", "title": "Systems thinking and system traps", "url": "https://bytepawn.com/systems-thinking.html", "published_at": "2016-01-05T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014eeb9e40", "title": "Luigi review", "url": "https://bytepawn.com/luigi.html", "published_at": "2015-12-19T23:00:00+00:00" }, { "id": "01a0875b-1678-7056-aa35-eb014f75923b", "title": "Cargo Cult Data", "url": "https://bytepawn.com/cargo-cult-data.html", "published_at": "2015-01-25T23:00:00+00:00" } ] posts Claim your blog
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Blog · corpus.blog/blogs/bytepawn.com/posts

Maro

bytepawn.com

2020

Small team planningoriginal ↗
9 Jan 2020

2019

Personal goalingoriginal ↗
21 Dec 2019
Pytorch in 2019original ↗
11 Dec 2019
Warren Buffett style fundamental metrics of long-term company performanceoriginal ↗
1 Dec 2019
Calibration curves for delivery prediction with Scikit-Learnoriginal ↗
20 Nov 2019
Using simulated self-play to solve all OpenAI Gym classic control problems with Pytorchoriginal ↗
13 Nov 2019
Applying policy gradient to OpenAI Gym classic control problems with Pytorchoriginal ↗
11 Nov 2019
Machine Learning at Fetchroriginal ↗
28 Oct 2019
Solving the CartPole Reinforcement Learning problem with Pytorchoriginal ↗
21 Oct 2019
Metrics Atlasoriginal ↗
28 Aug 2019
Playing Go with supervised learning in Pytorchoriginal ↗
24 Aug 2019
Arabic name classification with Scikit-Learn and Pytorchoriginal ↗
1 Aug 2019
Exploring prior beliefs with MCMCoriginal ↗
5 Jul 2019
A/B tests: Moving Fast vs Being Sureoriginal ↗
30 Jun 2019
Food deliveries, Bayes and Computational Statisticsoriginal ↗
21 Jun 2019
The Collatz conjectureoriginal ↗
1 Jun 2019
MNIST pixel attacks with Pytorchoriginal ↗
31 May 2019
Solving CIFAR-10 with Pytorch and SKLoriginal ↗
13 May 2019
Solving MNIST with Pytorch and SKLoriginal ↗
1 May 2019
SVM with Pytorchoriginal ↗
15 Apr 2019
Hacker News Embeddings with PyTorchoriginal ↗
11 Mar 2019
rxe: literate and composable regular expressionsoriginal ↗
1 Mar 2019
PyTorch Basics: Solving the Ax=b matrix equation with gradient descentoriginal ↗
7 Feb 2019
Automating a Call Center with Machine Learningoriginal ↗
26 Jan 2019
5 things that happened in Data Science in 2018original ↗
8 Jan 2019

2018

Warehouse locations with k-meansoriginal ↗
25 Sept 2018
Growth Accounting and Backtraced Growth Accountingoriginal ↗
15 Sept 2018
Fetchr Data Science Infra at 1 yearoriginal ↗
13 Aug 2018
What not to spend time onoriginal ↗
22 Jul 2018
Beat the averagesoriginal ↗
6 Jul 2018
Building the Fetchr Data Science Infra on AWS with Presto and Airfloworiginal ↗
13 Mar 2018

2016

Don’t build cockpits, become a coachoriginal ↗
8 Nov 2016
Beautiful A/B testingoriginal ↗
4 Jun 2016
Hack, HHVM and avoiding the Second-system effectoriginal ↗
13 May 2016
Einstein's amazing theoryoriginal ↗
15 Feb 2016
Heisengames and the importance of patience in businessoriginal ↗
7 Feb 2016
Cloud9: Cloud coding that actually worksoriginal ↗
6 Feb 2016
Luigi vs Airflow vs Pinballoriginal ↗
5 Feb 2016
Pinball revieworiginal ↗
5 Feb 2016
How to make a blog like thisoriginal ↗
6 Jan 2016
Airflow revieworiginal ↗
5 Jan 2016
Systems thinking and system trapsoriginal ↗
5 Jan 2016

2015

Luigi revieworiginal ↗
19 Dec 2015
Cargo Cult Dataoriginal ↗
25 Jan 2015
Previous