System Design Interview is an integral part of Software Engineer interviews and it takes a lot of time to prepare for System Design Interview questions. While there are people like Gaurav Sen who are doing a good job at teaching System Design concepts, I believe System Design Interviews are fundamentally broken. In this video, I'll explain Why.

Resources I talk about in this video:
1. Grokking the system interview: educative.io/courses/grokking-the-system-design-interview
2. Codekarle: youtube.com/c/codeKarle

NOTE: We are not paid by any of the above. Subscribe to our channel if you want to support us.

#systemdesign #systemdesigninterview #grokkingthesystemdesign

I have talked about how to learn System Design or High-Level Design(HLD) as a beginner. I have discussed what are the best resources for learning System Design like how to use educative.io courses. This will help you to transition from an SDE-1 to an SDE-2 role at any company.

I have covered all the concepts that are mandatory to learn system design and the standard problems you need to know before going to the interview.

Important Concepts
1. Scalability
2. Performance
3. Latency and Throughput
4. Consistency
5. Availability
6. Partition Tolerance
7. CAP Theorem
8. Domain Name System
9. Content Delivery Network
10. Load Balancers and Reverse Proxy
11. Microservices
12. Databases
13. Caching
14. Message Queues

System Design Primer - github.com/donnemartin/system-design-primer

Standard Questions
1. Pastebin
2. TinyURL
3. Uber
4. BookMyShow
5. Twitter Feed
6. Facebook Messenger
7. Search in Instagram
8. Video Streaming Service

Educative.io course - educative.io/courses/grokking-the-system-design-interview

System Design template - leetcode.com/discuss/career/229177/My-System-Design-Template

Netflix Blog - netflixtechblog.com/

Uber Engg Blog - eng.uber.com/

Google Developers - developers.googleblog.com/

High Scalability - highscalability.com/

Subscribe to my channel for more such videos :D

Join my Telegram link for interview preparation material and updates:
t.me/thecodeskool

You can also reach me at:

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instagram.com/thecodeskool/

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twitter.com/theCodeSkool

LinkedIn:
linkedin.com/in/deevankshu-garg-602501111/

As an excellent Machine Learning System Design example, I am going through the following paper:

"Recommending What Video to Watch Next: A Multitask Ranking System" by Google Inc. presented at RecSys 2019.

[PDF] daiwk.github.io/assets/youtube-multitask.pdf

// MY RECOMMENDATIONS:
Great "Machine Learning" Book:
📚 Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: amzn.to/3pwbjjE

Great "System Design" Book:
📚 Designing Data-Intensive Applications: amzn.to/3n05KYW

#machinelearning #systemdesign #recommendationsystem #recommendersystem #recommendation #rankingsystem #ranking #google #youtube #ai #ml #artificialintelligence #mlsystemdesign

Chip created the TensorFlow for Deep Learning Research course at Stanford University, has worked on the AI Applications team at Nvidia, and has published many popular resources for ML Engineers.
More videos at course.fullstackdeeplearning.com

Date of stream 22 Mar 2020.
Live-stream chat added as Subtitles/CC - English (Twitch Chat).
Stream title:
reverse engineering the coronavirus #lockdown

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- github.com/geohot/corona
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ncbi.nlm.nih.gov/nuccore/NC_045512
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NERSC Data Seminars: github.com/NERSC/data-seminars

Abstract: The majority of all materials data is currently scattered across the text, tables, and figures of millions of scientific publications. In my talk, I will present the work of our team at Lawrence Berkeley National Laboratory on the use of natural language processing (NLP) and machine learning techniques to extract and discover materials knowledge through textual analysis of the abstracts of several million journal articles. With this data we are exploring new avenues for materials discovery and design, such as how functional materials like thermoelectrics can be identified by using only unsupervised word embeddings for materials. To date, we have used advanced techniques for named entity recognition to extract more than 100 million mentions of materials, structures, properties, applications, synthesis methods, and characterization techniques from our database of over 3 million materials science abstracts. With this data, we are developing machine learning tools for autonomously building databases of materials-properties data extracted from unstructured materials text.

Feature Engineering for Recommender Systems
by Benedikt Schifferer (Nvidia), Chris Deotte (Nvidia) and Even Oldridge (Nvidia)

The selection of features and proper preparation of data for deep learning or machine learning models plays a significant role in the performance of recommender systems. To address this we propose a tutorial highlighting best practices and optimization techniques for feature engineering and preprocessing of recommender system datasets. The tutorial will explore feature engineering using pandas and Dask, and will also cover acceleration on the GPU using open source libraries like RAPIDS cuDF and NVTabular.

Date of stream 6 Dec 2020.
Live-stream chat added as Subtitles/CC - English (Twitch Chat).
Stream title: tinygrad: 2.8k stars! CIFAR, ANE, speed, memory management

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- github.com/geohot/tinygrad
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- ghidra-sre.org
- lldb.llvm.org
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M1 Chip with 8‑Core CPU
7‑Core GPU 256GB Storage
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How to get a job:
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How to collaborate:
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Buy things to support comma.ai:
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Are you interested in openpilot?
Knowledge base:
- wiki.comma.ai
Check out the code:
- openpilot.comma.ai
Is my car supported?
- comma.ai/vehicles
Frequently Asked Questions:
- comma.ai/faq
How to setup openpilot:
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Comma Secure Shell:
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CAN analysis tool:
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Review and annotate your driving data:
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- my.comma.ai/leaderboard
Comma Connect App:
- apps.apple.com/us/app/comma-connect/id1456551889
- play.google.com/store/apps/details?id=ai.comma.connect
Research:
- github.com/commaai/comma2k19
- github.com/commaai/comma10k
- github.com/commaai/research

Official George Hotz communication channels:
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- twitter.com/realGeorgeHotz

We archive George Hotz and comma.ai videos for fun.
Follow for notifications:
- twitter.com/geohotarchive
Unofficial communities and resources:
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- commasupport.zendesk.com

Thank you for reading and using the SHOW MORE button.
We hope you enjoy watching George's videos as much as we do.
See you at the next video.

"Building Intelligent Computer Systems With Large Scale Deep Learning"

For the past five years, the Google Brain team (g.co/brain) has conducted research on difficult problems in artificial intelligence, on building large-scale computer systems for machine learning research, and, in collaboration with many teams at Google, on
applying our research and systems to dozens of Google products. Our group has opensourced the TensorFlow system (tensorflow.org), a widely popular system designed to easily express machine learning ideas, and to quickly train, evaluate and deploy machine learning systems. In this talk, I’ll highlight some of the design decisions we made in building TensorFlow; discuss research results produced within our group in areas such as computer vision, language understanding, translation, health care and robotics; and describe ways in which these ideas have been applied to a variety of problems in Google’s products, usually in close collaboration with other teams. I will also touch on some exciting areas of research that we are currently pursuing within our group. This talk describes joint work with many people at Google.

Project & Seminar, ETH Zürich, Spring 2022
Genome Sequencing on Mobile Devices ( safari.ethz.ch/projects_and_seminars/spring2022/doku.php?id=genome_seq_mobile)
Accelerating Genome Analysis with FPGAs, GPUs, and New Execution Paradigms ( safari.ethz.ch/projects_and_seminars/spring2022/doku.php?id=bioinformatics)

Meeting 3: Read Mapping
Lecturer: Professor Onur Mutlu ( people.inf.ethz.ch/omutlu/)
Lecturer: Dr. Mohammed Alser
Date: March 22, 2022

Meeting 3 Slides (pptx): safari.ethz.ch/projects_and_seminars/spring2022/lib/exe/fetch.php?media=alser-pns-genomics-spring2022-lecture3-read-mapping-afterlecture.pptx
Meeting 3 Slides (pdf): safari.ethz.ch/projects_and_seminars/spring2022/lib/exe/fetch.php?media=alser-pns-genomics-spring2022-lecture3-read-mapping-afterlecture.pdf

Recommended Reading:
====================
Intelligent Architectures for Intelligent Computing Systems
people.inf.ethz.ch/omutlu/pub/intelligent-architectures-for-intelligent-computingsystems-invited_paper_DATE21.pdf

A Modern Primer on Processing in Memory
people.inf.ethz.ch/omutlu/pub/ModernPrimerOnPIM_springer-emerging-computing-bookchapter21.pdf

RowHammer: A Retrospective
people.inf.ethz.ch/omutlu/pub/RowHammer-Retrospective_ieee_tcad19.pdf

RECOMMENDED LECTURE VIDEOS & PLAYLISTS:
========================================
Computer Architecture Fall 2021 Lectures Playlist:
youtube.com/watch?v=4yfkM_5EFgo&list=PL5Q2soXY2Zi-Mnk1PxjEIG32HAGILkTOF

Digital Design and Computer Architecture Spring 2021 Livestream Lectures Playlist:
youtube.com/watch?v=LbC0EZY8yw4&list=PL5Q2soXY2Zi_uej3aY39YB5pfW4SJ7LlN

Featured Lectures:
youtube.com/watch?v=jVYCchBGNVc&list=PL5Q2soXY2Zi8VrmOTz44l2WupethSdh-M&index=1

Interview with Professor Onur Mutlu:
youtube.com/watch?v=8ffSEKZhmvo&list=PL5Q2soXY2Zi8VrmOTz44l2WupethSdh-M&index=9

The Story of RowHammer Lecture:
youtube.com/watch?v=sgd7PHQQ1AI&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=39

Accelerating Genome Analysis Lecture:
youtube.com/watch?v=r7sn41lH-4A&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=41

Memory-Centric Computing Systems Tutorial at IEDM 2021:
youtube.com/watch?v=H3sEaINPBOE&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=35

Intelligent Architectures for Intelligent Machines Lecture:
youtube.com/watch?v=GTieZPY4Wmc&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=38

Computer Architecture Fall 2020 Lectures Playlist:
youtube.com/watch?v=c3mPdZA-Fmc&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN

Digital Design and Computer Architecture Spring 2020 Lectures Playlist:
youtube.com/watch?v=AJBmIaUneB0&list=PL5Q2soXY2Zi_FRrloMa2fUYWPGiZUBQo2

Public Lectures by Onur Mutlu, Playlist:
youtube.com/watch?v=kgiZlSOcGFM&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl

Computer Architecture at Carnegie Mellon Spring 2015 Lectures Playlist:
youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq

Rethinking Memory System Design Lecture @stanfordonline :
youtube.com/watch?v=F7xZLNMIY1E&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=4

SAFARI Newsletter December 2021 ( safari.ethz.ch/safari-newsletter-december-2021/)
"Meet our Members" with Mohammed Alser ( mealser.github.io)
"Architecting for the Pandemic: Rethinking Genome Analysis at Population Scale"

Talk slides (pptx): safari.ethz.ch/safari_public_wp/wp-content/uploads/MohammedAlser-SAFARINewsletter-20-Dec-2021.pptx
Talk slides (pdf): safari.ethz.ch/safari_public_wp/wp-content/uploads/MohammedAlser-SAFARINewsletter-20-Dec-2021.pdf

More details on read mapping/alignment "Technology dictates algorithms: Recent developments in read alignment" from Genome Biology, August 2021
genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02443-7

Related Survey paper from IEEE Micro, Sep/Oct 2020:
people.inf.ethz.ch/omutlu/pub/AcceleratingGenomeAnalysis_ieeemicro20.pdf

Computer Architecture, Fall 2021, Lecture 10 Intelligent Genome Analysis (ETH Zürich, Fall 2021)
youtube.com/watch?v=tm-IRYa14qs

Computer Architecture, Fall 2020, Lecture 3a Introduction to Genome Sequence Analysis (ETH Zürich, Fall 2020)
youtube.com/watch?v=CrRb32v7SJc&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN&index=5

Computer Architecture, Fall 2020, Lecture 8 Intelligent Genome Analysis (ETH Zürich, Fall 2020)
youtube.com/watch?v=ygmQpdDTL7o&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN&index=14

Seminar in Computer Architecture, Fall 2021, Lecture 2 GateKeeper and Fast Genome Analysis (ETH Zürich, Fall 2021)
youtube.com/watch?v=jk1oUexuHRg

Computer Architecture, Fall 2020, Lecture 9a GenASM: Approx. String Matching Accelerator (ETH Zürich, Fall 2020)
youtube.com/watch?v=XoLpzmN-Pas&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN&index=15

Accelerating Genomics Project Course, Fall 2020, Lecture 1 Accelerating Genomics (ETH Zürich, Fall 2020)
youtube.com/watch?v=rgjl8ZyLsAg&list=PL5Q2soXY2Zi9E2bBVAgCqLgwiDRQDTyId

GenASM: Approx. String Matching Accelerator (ETH Zürich, Fall 2020)
youtube.com/watch?v=XoLpzmN-Pas&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN&t=0s

COVIDHunter: An Accurate, Flexible, Environment-Aware Open-Source COVID-19 Outbreak Simulation Model (ISMB/ECCB 2021, Virtual, July 2021)
youtube.com/watch?v=dKu65ydlBjw

Recommended Reading:
====================
Intelligent Architectures for Intelligent Computing Systems
people.inf.ethz.ch/omutlu/pub/intelligent-architectures-for-intelligent-computingsystems-invited_paper_DATE21.pdf

A Modern Primer on Processing in Memory
people.inf.ethz.ch/omutlu/pub/ModernPrimerOnPIM_springer-emerging-computing-bookchapter21.pdf

RowHammer: A Retrospective
people.inf.ethz.ch/omutlu/pub/RowHammer-Retrospective_ieee_tcad19.pdf

RECOMMENDED LECTURE VIDEOS & PLAYLISTS:
========================================
Computer Architecture Fall 2021 Lectures Playlist:
youtube.com/watch?v=4yfkM_5EFgo&list=PL5Q2soXY2Zi-Mnk1PxjEIG32HAGILkTOF

Digital Design and Computer Architecture Spring 2021 Livestream Lectures Playlist:
youtube.com/watch?v=LbC0EZY8yw4&list=PL5Q2soXY2Zi_uej3aY39YB5pfW4SJ7LlN

Featured Lectures:
youtube.com/watch?v=jVYCchBGNVc&list=PL5Q2soXY2Zi8VrmOTz44l2WupethSdh-M&index=1

Interview with Professor Onur Mutlu:
youtube.com/watch?v=8ffSEKZhmvo&list=PL5Q2soXY2Zi8VrmOTz44l2WupethSdh-M&index=9

The Story of RowHammer Lecture:
youtube.com/watch?v=sgd7PHQQ1AI&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=39

Accelerating Genome Analysis Lecture:
youtube.com/watch?v=r7sn41lH-4A&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=41

Memory-Centric Computing Systems Tutorial at IEDM 2021:
youtube.com/watch?v=H3sEaINPBOE&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=35

Intelligent Architectures for Intelligent Machines Lecture:
youtube.com/watch?v=GTieZPY4Wmc&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=38

Computer Architecture Fall 2020 Lectures Playlist:
youtube.com/watch?v=c3mPdZA-Fmc&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN

Digital Design and Computer Architecture Spring 2020 Lectures Playlist:
youtube.com/watch?v=AJBmIaUneB0&list=PL5Q2soXY2Zi_FRrloMa2fUYWPGiZUBQo2

Public Lectures by Onur Mutlu, Playlist:
youtube.com/watch?v=kgiZlSOcGFM&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl

Computer Architecture at Carnegie Mellon Spring 2015 Lectures Playlist:
youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq

Rethinking Memory System Design Lecture @stanfordonline :
youtube.com/watch?v=F7xZLNMIY1E&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=4

Project & Seminar, ETH Zürich, Spring 2022
Hands-on Acceleration on Heterogeneous Computing Systems ( safari.ethz.ch/projects_and_seminars/spring2022/doku.php?id=heterogeneous_systems)

Lecture 1: Hands-on Acceleration on Heterogeneous Computing Systems
Lecturer: Dr. Juan Gómez Luna
Lecturer: Professor Onur Mutlu ( people.inf.ethz.ch/omutlu/)
Date: March 15, 2022

Lecture 1 Slides (pptx): safari.ethz.ch/projects_and_seminars/spring2022/lib/exe/fetch.php?media=p_s-hetsys-ss2022-meeting1-aftermeeting.pptx
Lecture 1 Slides (pdf): safari.ethz.ch/projects_and_seminars/spring2022/lib/exe/fetch.php?media=p_s-hetsys-ss2022-meeting1-aftermeeting.pdf

RECOMMENDED VIDEOS BELOW:
===========================

The Story of RowHammer Lecture:
youtube.com/watch?v=sgd7PHQQ1AI&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=39

Accelerating Genome Analysis Lecture:
youtube.com/watch?v=r7sn41lH-4A&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=41

Memory-Centric Computing Systems Tutorial:
youtube.com/watch?v=H3sEaINPBOE&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=35

Intelligent Architectures for Intelligent Machines Lecture:
youtube.com/watch?v=GTieZPY4Wmc&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=38

Digital Design and Computer Architecture Spring 2021 Livestream Lectures Playlist:
youtube.com/watch?v=LbC0EZY8yw4&list=PL5Q2soXY2Zi_uej3aY39YB5pfW4SJ7LlN

Computer Architecture Fall 2020 Lectures Playlist:
youtube.com/watch?v=c3mPdZA-Fmc&list=PL5Q2soXY2Zi9xidyIgBxUz7xRPS-wisBN

Digital Design and Computer Architecture Spring 2020 Lectures Playlist:
youtube.com/watch?v=AJBmIaUneB0&list=PL5Q2soXY2Zi_FRrloMa2fUYWPGiZUBQo2

Rethinking Memory System Design Lecture @stanfordonline :
youtube.com/watch?v=F7xZLNMIY1E&list=PL5Q2soXY2Zi8D_5MGV6EnXEJHnV2YFBJl&index=4

Computer Architecture at Carnegie Mellon Spring 2015 Lectures Playlist:
youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq

Collaborative research by GWU and Arm bringing fast, memory efficient, and predictable Web Assembly execution to microcontrollers!

Authors: Gregor Peach, Runyu Pan, Zhuoyi Wu, Gabriel Parmer, Christopher Haster and Lucy Cherkasova

Read more in the paper: www2.seas.gwu.edu/~gparmer/publications/emsoft20wasm.pdf
...and find the code at: github.com/gwsystems/awsm

Presented at MobiSys 2021.

Are you looking for a job and feeling overwhelmed? You are not alone!

This webinar will unpack some of our best tips to help you navigate your job search, especially during these unprecedented times. Some of the topics we will cover are:

- Resume optimization
- Finding short-term work for your resume/portfolios
- Making connections and building your network
- Cold emailing
- Informational interviews
- and staying positive throughout everything

Pathrise (YC W'18) is a career accelerator that helps students and professionals land their dream job in tech. We work with people looking for positions in software engineering, product design, product management, marketing, strategy, and operations. Job-seekers in the program work 1-on-1 with industry and career mentors on everything they need to successfully navigate the job search. We have helped over 500 people land incredible jobs at Google, Facebook, Amazon, Salesforce, Uber, Atlassian, Microsoft, Nike, and many startups.

Learn more about us at pathrise.com.

EECS Colloquium
Wednesday, November 28 2018
306 Soda Hall (HP Auditorium)
4-5p

Captions available upon request.

On Tuesday, September 25th, Jeff Dean, Head of Google AI and Google Brain, visited heidelberg.ai ( heidelberg.ai) at the German Cancer Research Center in Heidelberg:

For the past seven years, the Google Brain team has conducted research on difficult problems in artificial intelligence, on building large-scale computer systems for machine learning research, and, in collaboration with many teams at Google, on applying our research and systems to many Google products. Our group has open-sourced the TensorFlow system, a widely popular system designed to easily express machine learning ideas, and to quickly train, evaluate and deploy machine learning systems. We have also collaborated closely with Google's platforms team to design and deploy new computational hardware called Tensor Processing Units, specialized for accelerating machine learning computations. In this talk, I'll highlight some of our research accomplishments, and will relate them to the National Academy of Engineering's Grand Engineering Challenges for the 21st Century, including the use of machine learning for healthcare, robotics, and engineering the tools of scientific discovery. I'll also cover how machine learning is transforming many aspects of our computing hardware and software systems.

This talk describes joint work with many people at Google.