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iamshreeram / ml-recs.md
Created July 22, 2020 16:06 — forked from bsletten/ml-recs.md
Machine Learning Path Recommendations

This is an incomplete, ever-changing curated list of content to assist people into the worlds of Data Science and Machine Learning. If you have a recommendation for something to add, please let me know. If something isn't here, it doesn't mean I don't recommend it, I just may not have had a chance to review it yet or not.

I will generally list things in order of easier to more formal/challenging content.

It may feel like there is an overwhelming amount of stuff for you to learn (because there is). But, there is a guided path that will get you there in time. You need to focus on Linear Algebra, Calculus, Statistics and probably Python (or R). Your best bet is to get a Safari Books Online account (https://www.safaribooksonline.com) which you may already have access to through school or work. If not, it is a reasonable way to get access to a tremendous number of books and videos.

I'm not saying you will get what you need out of everything here, but I have read/watched at least some of all of the following an

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iamshreeram / prereqs-self-driving-kubernetes.md
Created June 25, 2019 18:56 — forked from StevenACoffman/prereqs-self-driving-kubernetes.md
Prerequisites

Automated Infrastructure

This workshop will provide hands on experience on setting up and running an AWS Kubernetes cluster using EKS. We will use gitops, and explore kubernetes tools to make the cluster self-driving, with automated management and remedy of common cluster level problems. To achieve this, we will use eksctl, cluster-autoscaler, kube-prometheus (prometheus operator), node-problem-detector, draino, and node-local-dns-cache.

Intended audience

This workshop is intended to appeal primarily to four types of people:

  1. Application developers looking to get an AWS kubernetes cluster to experiment without a lot of infrastructure knowledge
  2. AWS DevOps people without a lot of kubernetes experience
  3. Kubernetes DevOps people without a lot of AWS experience
  4. Full-stack, Full-cycle developers in small or large teams.
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iamshreeram / fluent-filebeat-comparison.md
Created June 25, 2019 18:56 — forked from StevenACoffman/fluent-filebeat-comparison.md
Fluentd Fluent-bit FileBeat memory and cpu resources

Fluent-bit rocks

A short survey of log collection options and why you picked the wrong one. 😜

Who am I? Where am I from?

I'm Steve Coffman and I work at Ithaka. We do JStor (academic journals) and other stuff. How big is it?

Number what it means
101,332,633 unique visitors in 2017
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iamshreeram / dep.md
Created May 24, 2019 02:05 — forked from subfuzion/dep.md
Concise guide to golang/dep

Overview

This gist is based on the information available at golang/dep, only slightly more terse and annotated with a few notes and links primarily for my own personal benefit. It's public in case this information is helpful to anyone else as well.

I initially advocated Glide for my team and then, more recently, vndr. I've also taken the approach of exerting direct control over what goes into vendor/ in my Dockerfiles, and also work from isolated GOPATH environments on my system per project to ensure that dependencies are explicitly found under vendor/.

At the end of the day, vendoring (and committing vendor/) is about being in control of your dependencies and being able to achieve reproducible builds. While you can achieve this manually, things that are nice to have in a vendoring tool include:

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iamshreeram / README-Template.md
Created May 1, 2018 04:07 — forked from PurpleBooth/README-Template.md
A template to make good README.md

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

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iamshreeram / README.rst
Created November 16, 2017 23:37 — forked from dupuy/README.rst
Common markup for Markdown and reStructuredText

Markdown and reStructuredText

GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.

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iamshreeram / pyget2.py
Created September 25, 2016 02:55 — forked from benhutchins/pyget2.py
A python download accelerator
#!/usr/bin/env python
#
# pyget2.py
# A python download accelerator
#
# This file uses multiprocessing along with
# chunked/parallel downloading to speed up
# the download of files (if possible).
#
# @author Benjamin Hutchins
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iamshreeram / gist:ac84dbbbfa9581f7f4a99fe6446ba746
Created August 7, 2016 23:28 — forked from ashwanthkumar/gist:f04b1e45aaf880b6d363

The Ying-Yang of CEOs and Engineers

All successful startups begin with two founders. One guy is the Engineer, and the other guy is the business dude. Over the years of working with various people, I've learned what makes a good engineer, and what makes a good business dude, and the two are complete opposites of each other.

CEO Engineer