If you're into deep learning, then you know that students usually one of the two paths:
- Computer vision
- Natural language processing (NLP)
If you're into NLP, here are 5 fundamental concepts you should know:
ππ
https://t.me/generativeai_gpt/7
- Computer vision
- Natural language processing (NLP)
If you're into NLP, here are 5 fundamental concepts you should know:
ππ
https://t.me/generativeai_gpt/7
π1
If I were to start Computer Science in 2023,
- Harvard - Stanford
- MIT - IBM - Telegram
- Microsoft - Google
β― CS50 from Harvard
http://cs50.harvard.edu/x/2023/certificate/
β― C/C++
http://ocw.mit.edu/courses/6-s096-effective-programming-in-c-and-c-january-iap-2014/
β― Python
http://cs50.harvard.edu/python/2022/
https://t.me/dsabooks
β― SQL
http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql
https://t.me/sqlanalyst
β― DSA
http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/
https://t.me/crackingthecodinginterview/290
β― Java
http://learn.microsoft.com/shows/java-for-beginners/
https://t.me/Java_Programming_Notes
β― JavaScript
http://learn.microsoft.com/training/paths/web-development-101/
https://t.me/javascript_courses
β― TypeScript
http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/
β― C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07
β― Mathematics (incl. Statistics)
ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum
β― Data Science
cognitiveclass.ai/courses/data-science-101
https://t.me/datasciencefun/1141
β― Machine Learning
http://developers.google.com/machine-learning/crash-course
β― Deep Learning
introtodeeplearning.com
t.me/machinelearning_deeplearning/
β― Full Stack Web (HTML/CSS)
pll.harvard.edu/course/cs50s-web-programming-python-and-javascript/2023-05
t.me/webdevcoursefree/594
β― OS, Networking
ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/
β― Compiler Design
online.stanford.edu/courses/soe-ycscs1-compilers
Please give us credits while sharing: -> https://t.me/free4unow_backup
ENJOY LEARNING ππ
- Harvard - Stanford
- MIT - IBM - Telegram
- Microsoft - Google
β― CS50 from Harvard
http://cs50.harvard.edu/x/2023/certificate/
β― C/C++
http://ocw.mit.edu/courses/6-s096-effective-programming-in-c-and-c-january-iap-2014/
β― Python
http://cs50.harvard.edu/python/2022/
https://t.me/dsabooks
β― SQL
http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql
https://t.me/sqlanalyst
β― DSA
http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/
https://t.me/crackingthecodinginterview/290
β― Java
http://learn.microsoft.com/shows/java-for-beginners/
https://t.me/Java_Programming_Notes
β― JavaScript
http://learn.microsoft.com/training/paths/web-development-101/
https://t.me/javascript_courses
β― TypeScript
http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/
β― C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07
β― Mathematics (incl. Statistics)
ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum
β― Data Science
cognitiveclass.ai/courses/data-science-101
https://t.me/datasciencefun/1141
β― Machine Learning
http://developers.google.com/machine-learning/crash-course
β― Deep Learning
introtodeeplearning.com
t.me/machinelearning_deeplearning/
β― Full Stack Web (HTML/CSS)
pll.harvard.edu/course/cs50s-web-programming-python-and-javascript/2023-05
t.me/webdevcoursefree/594
β― OS, Networking
ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/
β― Compiler Design
online.stanford.edu/courses/soe-ycscs1-compilers
Please give us credits while sharing: -> https://t.me/free4unow_backup
ENJOY LEARNING ππ
π13β€5
How do you start AI and ML ?
Where do you go to learn these skills? What courses are the best?
Thereβs no best answerπ₯Ί. Everyoneβs path will be different. Some people learn better with books, others learn better through videos.
Whatβs more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, youβve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what Iβve tried every week new course lauch better than others its difficult to recommend any course
Iβve completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
Coursera - Deep Learning by Andrew Ng
fast.ai - Part 1and Part 2
Theyβre all world class. Iβm a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If youβre an absolute beginner, start with some introductory Python courses and when youβre a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.me/machinelearning_deeplearning
πTelegram Link: https://t.me/addlist/ID95piZJZa0wYzk5
Like for more β€οΈ
All the best ππ
Where do you go to learn these skills? What courses are the best?
Thereβs no best answerπ₯Ί. Everyoneβs path will be different. Some people learn better with books, others learn better through videos.
Whatβs more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, youβve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what Iβve tried every week new course lauch better than others its difficult to recommend any course
Iβve completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
Coursera - Deep Learning by Andrew Ng
fast.ai - Part 1and Part 2
Theyβre all world class. Iβm a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If youβre an absolute beginner, start with some introductory Python courses and when youβre a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.me/machinelearning_deeplearning
πTelegram Link: https://t.me/addlist/ID95piZJZa0wYzk5
Like for more β€οΈ
All the best ππ
π8β€3
Best Resource to Learn Artificial Intelligence (AI) For Free
ππ
https://imp.i115008.net/qn27PL
https://i.am.ai/roadmap
https://bit.ly/3h97QpE
https://t.me/datasciencefun/1375
http://microsoft.github.io/AI-For-Beginners
https://ai.google/education/
Share with credits: https://t.me/free4unow_backup
ENJOY LEARNING ππ
ππ
https://imp.i115008.net/qn27PL
https://i.am.ai/roadmap
https://bit.ly/3h97QpE
https://t.me/datasciencefun/1375
http://microsoft.github.io/AI-For-Beginners
https://ai.google/education/
Share with credits: https://t.me/free4unow_backup
ENJOY LEARNING ππ
π4
Machine Code for Beginners on the Amstrad 1984.pdf
85.1 MB
Machine Code for Beginners on the Amstrad
Steve Kramer, 1984
Steve Kramer, 1984
π3π₯1
Applied Generative AI for Beginners.pdf
7.9 MB
Applied Generative AI for Beginners
Akshay Kulkarni, 2023
Akshay Kulkarni, 2023
π3π₯1
Et_Tu_Code_Building,_Training_and_Hardware_for_LLM_AI_A_Comprehensive.pdf
59.3 MB
LLM Building Training Hardware
Et Tu Code, 2023
Et Tu Code, 2023
π7π₯1
Machine Learning, The Basics.pdf
3.3 MB
Machine Learning: The Basics
Alexander Jung, 2023
Alexander Jung, 2023
π12π₯4
Node.js Novice to Ninja by Craig Buckler (2022).pdf
7.5 MB
π7β€1π₯1
HAI_AI-Index-Report-2024.pdf
42.3 MB
Artificial Intelligence Index Report 2024
Ray Perrault, 2024
Ray Perrault, 2024
π7π₯1
Applied Causal Inference Powered by ML and AI, 2024.pdf
15.3 MB
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov, 2024
Victor Chernozhukov, 2024
π9π₯1
Machine Learning in Python for everyone.pdf
16.7 MB
π7β€2π₯1
Artificial Intelligence and Chatbots 101 (2024).pdf
1.3 MB
π Title: Artificial Intelligence and Chatbots 101 (2024)
Join for more: https://t.me/machinelearning_deeplearning
Join for more: https://t.me/machinelearning_deeplearning
π9β€1π₯1