An analysis of awcv9kjlh scwrlkjf4e
This is a page solely dedicated to awcv9kjlh scwrlkjf4e . This may not have any correlation to the rest of my website, but isn't that the beauty of randomness?
So say hello to this random new abstract idea! awcv9kjlh scwrlkjf4e forever
Also, be sure to check out this awesome file about this concept!
Research article on awcv9kjlh_scwrlkjf4e
Unable to view the video? Here is the link! https://www.youtube.com/watch?v=cksy13zw3UQ
I have also maintained a Github repository for those who might be interested! Github Link for awcv9kjlh scwrlkjf4e
This is a Quora excerpt of an post regarding ideas such as these : Abstract ideas are nonmaterial concepts that are detached from our human senses; they cannot be felt, heard, seen, touched, tasted, smelled, and yet they are significant aspects of human cognition and human culture. Examples include the ideas of love, democracy, freedom, history, government, and even the idea of an idea or of the mind itself. Because these concepts are disembodied from the empirical world, we can only test them indirectly. The fact that most human languages have a word for “ love” would, for example, be evidence that such a concept exists, or the ability of people who are not free to think about and even fight for “freedom” is indirect evidence that such a concept, while abstract, exists and has real-world consequences.
Also check out my other website on the people.tamu.edu domain for this task: girishk14's repository on awcv9kjlh scwrlkjf4e
Interested to know more? There are a whole lot of us working on this! My roommate's research on this topic
I will also share some of the interesting resources and videos from my research area.
- Intro to Natural Language Processing on Coursera by U of Michigan
- Intro to Artificial Intelligence course on Udacity which also covers NLP
- Deep Learning for Natural Language Processing (2015 classes) by Richard Socher
- Deep Learning for Natural Language Processing (2016 classes) by Richard Socher. Updated to make use of Tensorflow. Note that there are some lectures missing (lecture 9, and lectures 12 onwards).
- Natural Language Processing - course on Coursera that was only done in 2013. The videos are not available at the moment. Also Mike Collins is a great professor and his notes and lectures are very good.
- Statistical Machine Translation - a Machine Translation course with great assignments and slides.
- Udacity Deep Learning Deep Learning course on Udacity (using Tensorflow) which covers a section on using deep learning for NLP tasks (covering Word2Vec, RNN's and LSTMs).
- NLTK with Python 3 for Natural Language Processing by Harrison Kinsley(sentdex). Good tutorials with NLTK code implementation.
My friend Richa has also been working on this! Check it out!