le-dawg

# Not many mention this (I'm no expert so maybe there is a catch), but if your file has other streams like subtitles and other metadata like chapters and so on, it's possible to cut/trim and keep all streams with the following command

ffmpeg -to 60 -i input.mkv -map 0 -c copy output.mkv

// With -map 0 you take all the streams in the file, and with -c copy you copy all them as they are.
// Using -to omitting the start via -ss will cut the input video from start to **second 60.**
// Fiddling with map is useful also if you want only specific streams to be kept in the cut (maybe you don't need all the audio sources in the file, or only some subtitles).

le-dawg

Numerical Mathematics Study Guide

Part 1 of the TUHH Engineering Math Notes by by 0xdawg

Usage

The subdivisions or "Chapters" are clusters of knowledge around Numerical Mathematics, more or less strictly ordered by increasing specificity or involvedness. Use this to guide your learning journey around anything that involves calculations on computers with limited precision (the vast majority of cases). This is relevant for instance for complex computations involving a very large number of multiplication or division operations, especially when the sought values are in the [0..1] range.

Practical relevance for this lies in the training of neural networks and their deployment on less capable infrastructure, for instance. Other applications revolve around eigenvalue, singular value computations etc. as part of numerical simulations aka. interpolation, approximation, FEMs and other methods.

le-dawg

1stdibs.Com (XNAS:DIBS)
2 Arco Platform (XNAS:ARCE)
3 Bm Technologies (XNYS:BMTX)
4 Boston Omaha (XNAS:BOMN)
5 Cambium Networks (XNAS:CMBM)
6 Caribou (XNAS:CRBU)
7 Centessa Pharms (XNAS:CNTA)
8 CHICO’S FAS, INC. (XNYS:CHS)
9 Clearpoint Neuro (XNAS:CLPT)
10 Compass Pathways (XNAS:CMPS)

le-dawg

conda create -n NAME python=3.7.5 
conda activate NAME
conda install -c conda-forge pandas logging networkx matplotlib cadcad scipy numpy seaborn

le-dawg

So you want to mine in AWS without getting caught

tl;dr: AWS mining is against TOC so even if you have credits you will be invoiced and your credits burned. Watch out. These methods only help mitigate or lower the risk of discovery. Share responsibly.

Problem

AWS is firewalled af on top of the policy mentioned in tl;dr. A good way is to use a mining proxy with TLS. Even better would be a point-to-point VPN. Using VPN directly is also a good solution - but services that let you configure that you only want one certain port to run via VPN and not the SSH connection that is your lifeline are costly. This document sketches a few solutions, provides some links, and documents one particular approach. And remember, methods of detection will soon encompass deep learning: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9178288

le-dawg

le-dawg

# fix for mpl bug that cuts off/clips/clipping top/bottom of seaborn viz
b, t = plt.ylim() # discover the values for bottom and top
b += 0.5 # Add 0.5 to the bottom
t -= 0.5 # Subtract 0.5 from the top
plt.ylim(b, t) # update the ylim(bottom, top) values
plt.show() # ta-da!

# https://github.com/mwaskom/seaborn/issues/1773

le-dawg

Keybase proof

I hereby claim:

• I am le-dawg on github.
• I am truedawg (https://keybase.io/truedawg) on keybase.
• I have a public key ASCRWLIs65PdPP1f0Skwx0FVzT_-sPXO_srKeI-zndncjAo

To claim this, I am signing this object:

le-dawg

2018-11-30 05:31:50.350 [info] <0.13017.0>@aec_pow_cuckoo:generate_int_:214 Executing cmd: "./cuda29 -h 70684B536E66476C35763739436C67506E536E30517A4572694679354553722B367445573178497555796B3D71443150754864755743593D  -d 0"
2018-11-30 05:31:50.350 [info] <0.13018.0>@aec_pow_cuckoo:generate_int_:214 Executing cmd: "./cuda29 -h 70684B536E66476C35763739436C67506E536E30517A4572694679354553722B367445573178497555796B3D71443150754864755743593D  -d 1"
2018-11-30 05:31:50.351 [info] <0.13019.0>@aec_pow_cuckoo:generate_int_:214 Executing cmd: "./cuda29 -h 70684B536E66476C35763739436C67506E536E30517A4572694679354553722B367445573178497555796B3D71443150754864755743593D  -d 2"
2018-11-30 05:31:51.392 [debug] <0.13017.0>@aec_pow_cuckoo:parse_generation_result:479 GeForce GTX 1070 with 8118MB @ 256 bits x 4004MHz
2018-11-30 05:31:51.392 [debug] <0.13017.0>@aec_pow_cuckoo:parse_generation_result:479 Looking for 42-cycle on cuckoo30("phKSnfGl5v79ClgPnSn0QzEriFy5ESr+6tEW1xIuUyk=qD1PuHduWCY=",0) with 50% edges, 64*64 buckets, 17

le-dawg

grep -rlI git: . --exclude-dir={.git,.circleci,.gitattributes,.gitignore,.editorconfig} | xargs sed -i 's/git:/https:/g'