INFINITE.SKILLS.NATURAL.LANGUAGE.TEXT.PROCESSING.WITH.PYTHON-iLLiTERATE
- Section
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Appz
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- iLLiTERATE
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- 12
- Date
- 2018-12-14
NFO
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▓██ Natural Language Text Processing with Python ▓██
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▓██ ## Jonathan Mugan ▓██
▓██ ## Estimated time to complete: 1h 52m ▓██
▓██ ## Topics Natural Language Processing ▓██
▓██ ## Published byInfinite Skills 2017 ▓██
▓██ ▓██
▓██ ▓██
▓██ >> 2018x12 ▓██
▓██ >> 10x50 ▓██
▓██ >> +1 ▓██
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▓██▀▀ ▀▀▓██
▓██ // https://resources.oreilly.com/ ▓██
▓██ \\ https://www.safaribooksonline.com/ ▓██
▓██ // https://www.oreilly.com/ ▓██
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▓██ Even though computers can't read, they're very effective ▓██
▓██ at extracting information from natural language text. ▓██
▓██ They can determine the main themes in the text, figure ▓██
▓██ out if the writers of the text have positive or negative ▓██
▓██ feelings about what they've written, decide if two ▓██
▓██ documents are similar, add labels to documents, and ▓██
▓██ more. ▓██
▓██ ▓██
▓██ This course shows you how to accomplish some common NLP ▓██
▓██ (natural language processing) tasks using Python, an ▓██
▓██ easy to understand, general programming language, in ▓██
▓██ conjunction with the Python NLP libraries, NLTK, spaCy, ▓██
▓██ gensim, and scikit-learn. The course is designed for ▓██
▓██ basic level programmers with or without Python ▓██
▓██ experience. ▓██
▓██ ▓██
▓██ Gain practical hands-on natural language processing ▓██
▓██ experience using Python ▓██
▓██ Understand how to tokenize text so it can be ▓██
▓██ processed as symbols ▓██
▓██ Learn to convert text and words to vectors using ▓██
▓██ TF-IDF and word2vec ▓██
▓██ Explore dependency parsing, sentiment analysis, and ▓██
▓██ LDA topic modeling ▓██
▓██ Learn to find named entities in text and map them to ▓██
▓██ an external knowledge base ▓██
▓██ Understand the capabilities and limitations of ▓██
▓██ natural language text processing ▓██
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▓██ Jonathan Mugan is CEO and co-founder of DeepGrammar, a ▓██
▓██ natural language processing company. Jonathan has a PhD ▓██
▓██ in computer science from the University of Texas, and ▓██
▓██ has been working in AI and machine learning since 2003. ▓██
▓██ He describes his research focus as "making the squishy ▓██
▓██ reality of our everyday world available to computation." ▓██
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▓██ WEE ASUMME NO LIIABILLITY FUR A WROONG SPELING ▓██
▓██ COZ WEE ARRE A NON (iL)LiTERATE GRUP!! ▓██
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▓██ TANNKS TU THE LITERATE ASKII FRIIEND!! ▓██
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Files
| Path | Size |
| illiterate_iedmfgjfvfwyggzj.r00 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r01 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r02 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r03 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r04 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r05 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r06 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r07 | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.r08 | 36,69 MB |
| illiterate_iedmfgjfvfwyggzj.rar | 47,68 MB |
| illiterate_iedmfgjfvfwyggzj.sfv | 420 B |
| illiterate.nfo | 7,01 KB |