diff --git a/.all-contributorsrc b/.all-contributorsrc index 62791266..77413127 100644 --- a/.all-contributorsrc +++ b/.all-contributorsrc @@ -167,13 +167,6 @@ "profile": "https://github.com/DivyaAmirtharaj", "contributions": [] }, - { - "login": "ma3mool", - "name": "Abdulrahman Mahmoud", - "avatar_url": "https://avatars.githubusercontent.com/ma3mool", - "profile": "https://github.com/ma3mool", - "contributions": [] - }, { "login": "srivatsankrishnan", "name": "Srivatsan Krishnan", @@ -182,10 +175,17 @@ "contributions": [] }, { - "login": "arnaumarin", - "name": "marin-llobet", - "avatar_url": "https://avatars.githubusercontent.com/arnaumarin", - "profile": "https://github.com/arnaumarin", + "login": "ma3mool", + "name": "Abdulrahman Mahmoud", + "avatar_url": "https://avatars.githubusercontent.com/ma3mool", + "profile": "https://github.com/ma3mool", + "contributions": [] + }, + { + "login": "eezike", + "name": "Emeka Ezike", + "avatar_url": "https://avatars.githubusercontent.com/eezike", + "profile": "https://github.com/eezike", "contributions": [] }, { @@ -202,6 +202,13 @@ "profile": "https://github.com/James-QiuHaoran", "contributions": [] }, + { + "login": "arnaumarin", + "name": "marin-llobet", + "avatar_url": "https://avatars.githubusercontent.com/arnaumarin", + "profile": "https://github.com/arnaumarin", + "contributions": [] + }, { "login": "AditiR-42", "name": "Aditi Raju", @@ -209,13 +216,6 @@ "profile": "https://github.com/AditiR-42", "contributions": [] }, - { - "login": "jared-ni", - "name": "Jared Ni", - "avatar_url": "https://avatars.githubusercontent.com/jared-ni", - "profile": "https://github.com/jared-ni", - "contributions": [] - }, { "login": "MichaelSchnebly", "name": "Michael Schnebly", @@ -231,10 +231,10 @@ "contributions": [] }, { - "login": "Ekhao", - "name": "Emil Njor", - "avatar_url": "https://avatars.githubusercontent.com/Ekhao", - "profile": "https://github.com/Ekhao", + "login": "jared-ni", + "name": "Jared Ni", + "avatar_url": "https://avatars.githubusercontent.com/jared-ni", + "profile": "https://github.com/jared-ni", "contributions": [] }, { @@ -245,10 +245,10 @@ "contributions": [] }, { - "login": "BaeHenryS", - "name": "Henry Bae", - "avatar_url": "https://avatars.githubusercontent.com/BaeHenryS", - "profile": "https://github.com/BaeHenryS", + "login": "Ekhao", + "name": "Emil Njor", + "avatar_url": "https://avatars.githubusercontent.com/Ekhao", + "profile": "https://github.com/Ekhao", "contributions": [] }, { @@ -258,6 +258,13 @@ "profile": "https://github.com/leo47007", "contributions": [] }, + { + "login": "BaeHenryS", + "name": "Henry Bae", + "avatar_url": "https://avatars.githubusercontent.com/BaeHenryS", + "profile": "https://github.com/BaeHenryS", + "contributions": [] + }, { "login": "jaywonchung", "name": "Jae-Won Chung", @@ -272,20 +279,6 @@ "profile": "https://github.com/mmaz", "contributions": [] }, - { - "login": "Emeka Ezike", - "name": "Emeka Ezike", - "avatar_url": "https://www.gravatar.com/avatar/af39c27c6090c50a1921a9b6366e81cc?d=identicon&s=100", - "profile": "https://github.com/harvard-edge/cs249r_book/graphs/contributors", - "contributions": [] - }, - { - "login": "jzhou1318", - "name": "Jennifer Zhou", - "avatar_url": "https://avatars.githubusercontent.com/jzhou1318", - "profile": "https://github.com/jzhou1318", - "contributions": [] - }, { "login": "euranofshin", "name": "Eura Nofshin", @@ -293,6 +286,13 @@ "profile": "https://github.com/euranofshin", "contributions": [] }, + { + "login": "marcozennaro", + "name": "Marco Zennaro", + "avatar_url": "https://avatars.githubusercontent.com/marcozennaro", + "profile": "https://github.com/marcozennaro", + "contributions": [] + }, { "login": "ShvetankPrakash", "name": "Shvetank Prakash", @@ -307,6 +307,13 @@ "profile": "https://github.com/arbass22", "contributions": [] }, + { + "login": "jzhou1318", + "name": "Jennifer Zhou", + "avatar_url": "https://avatars.githubusercontent.com/jzhou1318", + "profile": "https://github.com/jzhou1318", + "contributions": [] + }, { "login": "pongtr", "name": "Pong Trairatvorakul", @@ -314,13 +321,6 @@ "profile": "https://github.com/pongtr", "contributions": [] }, - { - "login": "marcozennaro", - "name": "Marco Zennaro", - "avatar_url": "https://avatars.githubusercontent.com/marcozennaro", - "profile": "https://github.com/marcozennaro", - "contributions": [] - }, { "login": "alex-oesterling", "name": "Alex Oesterling", @@ -385,10 +385,10 @@ "contributions": [] }, { - "login": "happyappledog", - "name": "happyappledog", - "avatar_url": "https://avatars.githubusercontent.com/happyappledog", - "profile": "https://github.com/happyappledog", + "login": "emmanuel2406", + "name": "Emmanuel Rassou", + "avatar_url": "https://avatars.githubusercontent.com/emmanuel2406", + "profile": "https://github.com/emmanuel2406", "contributions": [] }, { @@ -419,13 +419,6 @@ "profile": "https://github.com/YangZhou1997", "contributions": [] }, - { - "login": "jessicaquaye", - "name": "Jessica Quaye", - "avatar_url": "https://avatars.githubusercontent.com/jessicaquaye", - "profile": "https://github.com/jessicaquaye", - "contributions": [] - }, { "login": "jasonlyik", "name": "Jason Yik", @@ -434,10 +427,24 @@ "contributions": [] }, { - "login": "emmanuel2406", - "name": "Emmanuel Rassou", - "avatar_url": "https://avatars.githubusercontent.com/emmanuel2406", - "profile": "https://github.com/emmanuel2406", + "login": "happyappledog", + "name": "happyappledog", + "avatar_url": "https://avatars.githubusercontent.com/happyappledog", + "profile": "https://github.com/happyappledog", + "contributions": [] + }, + { + "login": "ciyer64", + "name": "Curren Iyer", + "avatar_url": "https://avatars.githubusercontent.com/ciyer64", + "profile": "https://github.com/ciyer64", + "contributions": [] + }, + { + "login": "jessicaquaye", + "name": "Jessica Quaye", + "avatar_url": "https://avatars.githubusercontent.com/jessicaquaye", + "profile": "https://github.com/jessicaquaye", "contributions": [] }, { @@ -454,6 +461,13 @@ "profile": "https://github.com/sjohri20", "contributions": [] }, + { + "login": "vijay-edu", + "name": "Vijay Edupuganti", + "avatar_url": "https://avatars.githubusercontent.com/vijay-edu", + "profile": "https://github.com/vijay-edu", + "contributions": [] + }, { "login": "vitasam", "name": "The Random DIY", @@ -475,13 +489,6 @@ "profile": "https://github.com/harvard-edge/cs249r_book/graphs/contributors", "contributions": [] }, - { - "login": "Vijay Edupuganti", - "name": "Vijay Edupuganti", - "avatar_url": "https://www.gravatar.com/avatar/b15b6e0e9adf58099905c1a0fd474cb9?d=identicon&s=100", - "profile": "https://github.com/harvard-edge/cs249r_book/graphs/contributors", - "contributions": [] - }, { "login": "Jothi Ramaswamy", "name": "Jothi Ramaswamy", @@ -496,13 +503,6 @@ "profile": "https://github.com/harvard-edge/cs249r_book/graphs/contributors", "contributions": [] }, - { - "login": "Curren Iyer", - "name": "Curren Iyer", - "avatar_url": "https://www.gravatar.com/avatar/bd53d146aa888548c8db4da02bf81e7a?d=identicon&s=100", - "profile": "https://github.com/harvard-edge/cs249r_book/graphs/contributors", - "contributions": [] - }, { "login": "Fatima Shah", "name": "Fatima Shah", diff --git a/README.md b/README.md index 94b7e488..5dc7c52b 100644 --- a/README.md +++ b/README.md @@ -116,36 +116,36 @@ This project follows the [all-contributors](https://allcontributors.org) specifi Colby Banbury
Colby Banbury

Zishen Wan
Zishen Wan

Divya Amirtharaj
Divya Amirtharaj

- Abdulrahman Mahmoud
Abdulrahman Mahmoud

Srivatsan Krishnan
Srivatsan Krishnan

+ Abdulrahman Mahmoud
Abdulrahman Mahmoud

- marin-llobet
marin-llobet

+ Emeka Ezike
Emeka Ezike

Aghyad Deeb
Aghyad Deeb

Haoran Qiu
Haoran Qiu

+ marin-llobet
marin-llobet

Aditi Raju
Aditi Raju

- Jared Ni
Jared Ni

Michael Schnebly
Michael Schnebly

oishib
oishib

- Emil Njor
Emil Njor

+ Jared Ni
Jared Ni

ELSuitorHarvard
ELSuitorHarvard

- Henry Bae
Henry Bae

+ Emil Njor
Emil Njor

Yu-Shun Hsiao
Yu-Shun Hsiao

+ Henry Bae
Henry Bae

Jae-Won Chung
Jae-Won Chung

Mark Mazumder
Mark Mazumder

- Emeka Ezike
Emeka Ezike

- Jennifer Zhou
Jennifer Zhou

+ Eura Nofshin
Eura Nofshin

- Eura Nofshin
Eura Nofshin

+ Marco Zennaro
Marco Zennaro

Shvetank Prakash
Shvetank Prakash

Andrew Bass
Andrew Bass

+ Jennifer Zhou
Jennifer Zhou

Pong Trairatvorakul
Pong Trairatvorakul

- Marco Zennaro
Marco Zennaro

Alex Oesterling
Alex Oesterling

@@ -159,31 +159,31 @@ This project follows the [all-contributors](https://allcontributors.org) specifi Sercan Aygün
Sercan Aygün

gnodipac886
gnodipac886

Baldassarre Cesarano
Baldassarre Cesarano

- happyappledog
happyappledog

+ Emmanuel Rassou
Emmanuel Rassou

Bilge Acun
Bilge Acun

abigailswallow
abigailswallow

yanjingl
yanjingl

Yang Zhou
Yang Zhou

- Jessica Quaye
Jessica Quaye

+ Jason Yik
Jason Yik

- Jason Yik
Jason Yik

- Emmanuel Rassou
Emmanuel Rassou

+ happyappledog
happyappledog

+ Curren Iyer
Curren Iyer

+ Jessica Quaye
Jessica Quaye

Sonia Murthy
Sonia Murthy

Shreya Johri
Shreya Johri

- The Random DIY
The Random DIY

+ Vijay Edupuganti
Vijay Edupuganti

+ The Random DIY
The Random DIY

Costin-Andrei Oncescu
Costin-Andrei Oncescu

Annie Laurie Cook
Annie Laurie Cook

- Vijay Edupuganti
Vijay Edupuganti

Jothi Ramaswamy
Jothi Ramaswamy

- Batur Arslan
Batur Arslan

- Curren Iyer
Curren Iyer

+ Batur Arslan
Batur Arslan

Fatima Shah
Fatima Shah

a-saraf
a-saraf

songhan
songhan

diff --git a/contents/about.qmd b/contents/about.qmd index ae4d33c0..047e1bf6 100644 --- a/contents/about.qmd +++ b/contents/about.qmd @@ -20,11 +20,11 @@ By the time you finish this book, we hope that you'll have a foundational unders This book is tailored for individuals at various stages in their interaction with machine learning systems. It starts with the fundamentals and progresses to more advanced topics pertinent to the ML community and broader research areas. The most relevant audiences include: -**Students in Computer Science and Electrical Engineering:** Senior and graduate students in these fields will find this book invaluable. It introduces the techniques used in designing and building ML systems, focusing on fundamentals rather than depth—typically the focus of classroom instruction. This book aims to provide the necessary background and context, enabling instructors to delve deeper into advanced topics. An important aspect is the end-to-end focus, often overlooked in traditional curricula. +* **Students in Computer Science and Electrical Engineering:** Senior and graduate students in these fields will find this book invaluable. It introduces the techniques used in designing and building ML systems, focusing on fundamentals rather than depth—typically the focus of classroom instruction. This book aims to provide the necessary background and context, enabling instructors to delve deeper into advanced topics. An important aspect is the end-to-end focus, often overlooked in traditional curricula. -**Systems Engineers:** For engineers, this book serves as a guide to understanding the challenges of intelligent applications, especially on resource-constrained ML platforms. It covers the conceptual framework and practical components that constitute an ML system, extending beyond specific areas you might specialize in at your job. +* **Systems Engineers:** For engineers, this book serves as a guide to understanding the challenges of intelligent applications, especially on resource-constrained ML platforms. It covers the conceptual framework and practical components that constitute an ML system, extending beyond specific areas you might specialize in at your job. -**Researchers and Academics:** Researchers will find that this book addresses the unique challenges of running machine learning algorithms on diverse platforms. Efficiency is becoming increasingly important; understanding algorithms alone is not sufficient, as a deeper understanding of systems is necessary to build more efficient models. For researchers, the book cites seminal papers, guiding you towards foundational works that have shaped the field and drawing connections between various areas with significant implications for your work. +* **Researchers and Academics:** Researchers will find that this book addresses the unique challenges of running machine learning algorithms on diverse platforms. Efficiency is becoming increasingly important; understanding algorithms alone is not sufficient, as a deeper understanding of systems is necessary to build more efficient models. For researchers, the book cites seminal papers, guiding you towards foundational works that have shaped the field and drawing connections between various areas with significant implications for your work. ## Key Learning Outcomes diff --git a/contents/contributors.qmd b/contents/contributors.qmd index 8bdad033..fbe4292b 100644 --- a/contents/contributors.qmd +++ b/contents/contributors.qmd @@ -103,36 +103,36 @@ We extend our sincere thanks to the diverse group of individuals who have genero Colby Banbury
Colby Banbury

Zishen Wan
Zishen Wan

Divya Amirtharaj
Divya Amirtharaj

- Abdulrahman Mahmoud
Abdulrahman Mahmoud

Srivatsan Krishnan
Srivatsan Krishnan

+ Abdulrahman Mahmoud
Abdulrahman Mahmoud

- marin-llobet
marin-llobet

+ Emeka Ezike
Emeka Ezike

Aghyad Deeb
Aghyad Deeb

Haoran Qiu
Haoran Qiu

+ marin-llobet
marin-llobet

Aditi Raju
Aditi Raju

- Jared Ni
Jared Ni

Michael Schnebly
Michael Schnebly

oishib
oishib

- Emil Njor
Emil Njor

+ Jared Ni
Jared Ni

ELSuitorHarvard
ELSuitorHarvard

- Henry Bae
Henry Bae

+ Emil Njor
Emil Njor

Yu-Shun Hsiao
Yu-Shun Hsiao

+ Henry Bae
Henry Bae

Jae-Won Chung
Jae-Won Chung

Mark Mazumder
Mark Mazumder

- Emeka Ezike
Emeka Ezike

- Jennifer Zhou
Jennifer Zhou

+ Eura Nofshin
Eura Nofshin

- Eura Nofshin
Eura Nofshin

+ Marco Zennaro
Marco Zennaro

Shvetank Prakash
Shvetank Prakash

Andrew Bass
Andrew Bass

+ Jennifer Zhou
Jennifer Zhou

Pong Trairatvorakul
Pong Trairatvorakul

- Marco Zennaro
Marco Zennaro

Alex Oesterling
Alex Oesterling

@@ -146,31 +146,31 @@ We extend our sincere thanks to the diverse group of individuals who have genero Sercan Aygün
Sercan Aygün

gnodipac886
gnodipac886

Baldassarre Cesarano
Baldassarre Cesarano

- happyappledog
happyappledog

+ Emmanuel Rassou
Emmanuel Rassou

Bilge Acun
Bilge Acun

abigailswallow
abigailswallow

yanjingl
yanjingl

Yang Zhou
Yang Zhou

- Jessica Quaye
Jessica Quaye

+ Jason Yik
Jason Yik

- Jason Yik
Jason Yik

- Emmanuel Rassou
Emmanuel Rassou

+ happyappledog
happyappledog

+ Curren Iyer
Curren Iyer

+ Jessica Quaye
Jessica Quaye

Sonia Murthy
Sonia Murthy

Shreya Johri
Shreya Johri

- The Random DIY
The Random DIY

+ Vijay Edupuganti
Vijay Edupuganti

+ The Random DIY
The Random DIY

Costin-Andrei Oncescu
Costin-Andrei Oncescu

Annie Laurie Cook
Annie Laurie Cook

- Vijay Edupuganti
Vijay Edupuganti

Jothi Ramaswamy
Jothi Ramaswamy

- Batur Arslan
Batur Arslan

- Curren Iyer
Curren Iyer

+ Batur Arslan
Batur Arslan

Fatima Shah
Fatima Shah

a-saraf
a-saraf

songhan
songhan

diff --git a/contents/dl_primer/dl_primer.qmd b/contents/dl_primer/dl_primer.qmd index b2b3803c..08718e5b 100644 --- a/contents/dl_primer/dl_primer.qmd +++ b/contents/dl_primer/dl_primer.qmd @@ -110,7 +110,7 @@ Multilayer perceptrons (MLPs) are an evolution of the single-layer perceptron mo While a single perceptron is limited in its capacity to model complex patterns, the real strength of neural networks emerges from the assembly of multiple layers. Each layer consists of numerous perceptrons working together, allowing the network to capture intricate and non-linear relationships within the data. With sufficient depth and breadth, these networks can approximate virtually any function, no matter how complex. -![Multilayer Perceptron. Source: Wikimedia - Charlie.](https://www.nomidl.com/wp-content/uploads/2022/04/image-7.png){width=70%, #fig-mlp} +![Multilayer Perceptron. Source: Wikimedia - Charlie.](https://www.nomidl.com/wp-content/uploads/2022/04/image-7.png){width=70% #fig-mlp} ### Training Process