Here is the list of resources to learn Data Structures and Algorithms from beginner to advance:
π Prerequisite - MIT's Mathematics for Computer Science:
πΈ https://lnkd.in/ejdPkSs
π Khan Academy - Intro to algorithms:
πΈ https://lnkd.in/e8ZUWwz
π Introduction to Algorithms Book by Charles E. Leiserson, Clifford Stein, Ronald Rivest, and Thomas H. Cormen:
πΈ https://lnkd.in/e8iqvwn
π GeeksforGeeks - Data Structures Tutorials:
πΈhttps://lnkd.in/eiFACVV
π MIT - Introduction to Algorithms:
πΈ https://lnkd.in/eKavb3T
π Coursera - Data Structures and Algorithms Specialization:
πΈ https://lnkd.in/eDk8ZuY
π Coursera - Algorithms Specialization:
πΈ https://lnkd.in/ejJw5TV
π MIT - Advanced Data Structures:
πΈ https://lnkd.in/eKA7FD2
π GeeksforGeeks - Advanced Data Structures Tutorials:
πΈ https://lnkd.in/eu2J-Bm
π‘ I also found this interesting website which explains Data Structures and Algorithms through animations -
πΈ https://visualgo.net/en
#datastructures #algorithms #mathematics #machinelearning #computerscience
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π Prerequisite - MIT's Mathematics for Computer Science:
πΈ https://lnkd.in/ejdPkSs
π Khan Academy - Intro to algorithms:
πΈ https://lnkd.in/e8ZUWwz
π Introduction to Algorithms Book by Charles E. Leiserson, Clifford Stein, Ronald Rivest, and Thomas H. Cormen:
πΈ https://lnkd.in/e8iqvwn
π GeeksforGeeks - Data Structures Tutorials:
πΈhttps://lnkd.in/eiFACVV
π MIT - Introduction to Algorithms:
πΈ https://lnkd.in/eKavb3T
π Coursera - Data Structures and Algorithms Specialization:
πΈ https://lnkd.in/eDk8ZuY
π Coursera - Algorithms Specialization:
πΈ https://lnkd.in/ejJw5TV
π MIT - Advanced Data Structures:
πΈ https://lnkd.in/eKA7FD2
π GeeksforGeeks - Advanced Data Structures Tutorials:
πΈ https://lnkd.in/eu2J-Bm
π‘ I also found this interesting website which explains Data Structures and Algorithms through animations -
πΈ https://visualgo.net/en
#datastructures #algorithms #mathematics #machinelearning #computerscience
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
Human Centered AI Initiative: a personal vision of how #neuroscience #psychology #ai #physics #mathematics and other fields can work together to both understand biological intelligence and create artificial intelligence! https://hai.stanford.edu/news/the_intertwined_quest_for_understanding_biological_intelligence_and_creating_artificial_intelligence/
β΄οΈ @AI_Python_EN
π£ @AI_Python_Arxiv
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π£ @AI_Python_Arxiv
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On intelligence: its creation and understanding
The intertwined quest for understanding biological intelligence and creating artificial intelligence.
By Surya Ganguli, Stanford Human Centered AI Initiative:
https://lnkd.in/ezciPda
#neuroscience #ai #physics #mathematics
β΄οΈ @AI_Python_EN
π£ @AI_Python_Arxiv
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The intertwined quest for understanding biological intelligence and creating artificial intelligence.
By Surya Ganguli, Stanford Human Centered AI Initiative:
https://lnkd.in/ezciPda
#neuroscience #ai #physics #mathematics
β΄οΈ @AI_Python_EN
π£ @AI_Python_Arxiv
βοΈ @AI_Python
Interested in research on the interface of #evolution, systems and molecular #biology, #mathematics, and #statistics? Apply now to join the Evolutionary Dynamics lab IGCiencia as a postdoc, programmer, or PhD student! https://evoldynamics.org/positions Please spread the word!
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π£ @AI_Python_arXiv
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π£ @AI_Python_arXiv
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Foundations Built for a General Theory of Neural Networks
"Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural networkβs form will influence its function."
Article by Kevin Hartnett: https://lnkd.in/eZa5eyX
#artificialneuralnetworks #artificalintelligence #deeplearning #neuralnetworks #mathematics
βοΈ @AI_Python
π£ @AI_Python_Arxiv
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"Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural networkβs form will influence its function."
Article by Kevin Hartnett: https://lnkd.in/eZa5eyX
#artificialneuralnetworks #artificalintelligence #deeplearning #neuralnetworks #mathematics
βοΈ @AI_Python
π£ @AI_Python_Arxiv
β΄οΈ @AI_Python_EN
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A Brief History of Data Science (Pre-2010, i.e. prior to rise of deep learning & popular usage of the term "data science")
#
Note: Modified original version of infographic to add 3 seminal developments in the history of Artificial Intelligence:
- 1943: Artificial neuron model (McCulloch & Pitts)
- 1950: Turing Test (Alan Turing)
- 1956: Dartmouth Conference (McCarthy, Minsky, Shannon)
#datascience #statistics #analytics #machinelearning #bigdata #artificialintelligence #innovation #technology #history #ai #datamining #informatics #infographics #informationtechnology #computerscience #dataanalysis #deeplearning #neuroscience #mathematics #science
π£ @AI_Python_Arxiv
β΄οΈ @AI_Python_EN
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#
Note: Modified original version of infographic to add 3 seminal developments in the history of Artificial Intelligence:
- 1943: Artificial neuron model (McCulloch & Pitts)
- 1950: Turing Test (Alan Turing)
- 1956: Dartmouth Conference (McCarthy, Minsky, Shannon)
#datascience #statistics #analytics #machinelearning #bigdata #artificialintelligence #innovation #technology #history #ai #datamining #informatics #infographics #informationtechnology #computerscience #dataanalysis #deeplearning #neuroscience #mathematics #science
π£ @AI_Python_Arxiv
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Here is a #MachineLearning math quiz for you.
There are several loss functions (0-1, logarithmic, quadratic, exponential etc) and there is a risk function as well.
Can you define your own loss function?
#mathematics #deeplearning
#ai
β΄οΈ @AI_Python_EN
There are several loss functions (0-1, logarithmic, quadratic, exponential etc) and there is a risk function as well.
Can you define your own loss function?
#mathematics #deeplearning
#ai
β΄οΈ @AI_Python_EN
Mish is now even supported on YOLO v3 backend. Couldn't have been more elated with how rewarding this project has been. Link to repository -
https://github.com/digantamisra98/Mish
#neuralnetworks #mathematics #algorithms #deeplearning #machinelearning
βοΈ @AI_Python_EN
https://github.com/digantamisra98/Mish
#neuralnetworks #mathematics #algorithms #deeplearning #machinelearning
βοΈ @AI_Python_EN
MIT Technology Review:
A #NeuralNet solves the three-body problem 100 million times faster
#MachineLearning #mathematics
π° NeuralNet
π° Paper
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A #NeuralNet solves the three-body problem 100 million times faster
#MachineLearning #mathematics
π° NeuralNet
π° Paper
βοΈ @AI_Python_EN