Garis besar topik

  • Part of Speech

    1. Reading and Vocabulary

    2. Grammar focus : Verbal and  nominal sentence

    3. Writing : Making a short sentence based on verbal and nominal sentence and part of speech


    • Reading text : Natural Language Pelajaran
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      What is NLP?

      Natural language processing, or NLP, combines computational linguisticsΓÇörule-based modeling of human languageΓÇöwith statistical and machine learning models to enable computers and digital devices to recognize, understand and generate text and speech.

      A branch of artificial intelligence (AI), NLP lies at the heart of applications and devices that can

      • translate text from one language to another
      • respond to typed or spoken commands
      • recognize or authenticate users based on voice
      • summarize large volumes of text
      • assess the intent or sentiment of text or speech
      • generate text or graphics or other content on demand

      often in real time. Today most people have interacted with NLP in the form of voice-operated GPS systems, digital assistants, speech-to-text dictation software, customer service chatbots, and other consumer conveniences. But NLP also plays a growing role in enterprise solutions that help streamline and automate business operations, increase employee productivity, and simplify mission-critical business processes.

      NLP use cases

      Natural language processing is the driving force behind machine intelligence in many modern real-world applications. Here are a few examples:

      • Spam detection: You may not think of spam detection as an NLP solution, but the best spam detection technologies use NLP's text classification capabilities to scan emails for language that often indicates spam or phishing. These indicators can include overuse of financial terms, characteristic bad grammar, threatening language, inappropriate urgency, misspelled company names, and more. Spam detection is one of a handful of NLP problems that experts consider 'mostly solved' (although you may argue that this doesnΓÇÖt match your email experience).
      • Machine translation: Google Translate is an example of widely available NLP technology at work. Truly useful machine translation involves more than replacing words in one language with words of another.  Effective translation has to capture accurately the meaning and tone of the input language and translate it to text with the same meaning and desired impact in the output language. Machine translation tools are making good progress in terms of accuracy. A great way to test any machine translation tool is to translate text to one language and then back to the original. An oft-cited classic example: Not long ago, translating ΓÇ£The spirit is willing but the flesh is weakΓÇ¥ from English to Russian and back yielded ΓÇ£The vodka is good but the meat is rotten.ΓÇ¥ Today, the result is ΓÇ£The spirit desires, but the flesh is weak,ΓÇ¥ which isnΓÇÖt perfect, but inspires much more confidence in the English-to-Russian translation.
      • Virtual agents and chatbots: Virtual agents such as Apple's Siri and Amazon's Alexa use speech recognition to recognize patterns in voice commands and natural language generation to respond with appropriate action or helpful comments. Chatbots perform the same magic in response to typed text entries. The best of these also learn to recognize contextual clues about human requests and use them to provide even better responses or options over time. The next enhancement for these applications is question answering, the ability to respond to our questionsΓÇöanticipated or notΓÇöwith relevant and helpful answers in their own words.
      • Social media sentiment analysis: NLP has become an essential business tool for uncovering hidden data insights from social media channels. Sentiment analysis can analyze language used in social media posts, responses, reviews, and more to extract attitudes and emotions in response to products, promotions, and eventsΓÇôinformation companies can use in product designs, advertising campaigns, and more.
      • Text summarization: Text summarization uses NLP techniques to digest huge volumes of digital text and create summaries and synopses for indexes, research databases, or busy readers who don't have time to read full text. The best text summarization applications use semantic reasoning and natural language generation (NLG) to add useful context and conclusions to summaries.

    • Grammar focus : Verbal and Nominal Sentence Pelajaran
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      Nominal sentence is a sentence that have not a verb, but can be an adjective, noun or adverb, then the nominal sentence needs auxiliary verb, such as is, am, are, and it is followed by adjectives/ adverb/ noun. Verbal sentence is subject followed by verb.


      Kalimat verbal dan nominal adalah pengetahuan dasar Bahasa Inggris yang wajib dipelajari. Sama halnya dengan Bahasa Indonesia, Bahasa Inggris juga memiliki tata bahasa sesuai kaidahnya. Materi ini merupakan salah satu materi pokok dalam penyusunan kosa kata yang tepat dalam Bahasa Inggris. 

      Kalimat verbal dan nominal adalah pengetahuan dasar Bahasa Inggris yang wajib dipelajari. Sama halnya dengan Bahasa Indonesia, Bahasa Inggris juga memiliki tata bahasa sesuai kaidahnya. Materi ini merupakan salah satu materi pokok dalam penyusunan kosa kata yang tepat dalam Bahasa Inggris. Sehingga bagi para pemula, mempelajari materi ini juga sangat diperlukan. Tapi apa sih kalimat verbal dan nominal itu? Nah di artikel kali ini kita akan membahas tentang kalimat verbal dan nominal.

      ΓÇó Definisi kalimat

      Kalimat adalah kata-kata yang minimal terdiri dari subyek dan predikat. Jenis kalimat sendiri ada dua yaitu kalimat verbal dan nominal.

       

      ΓÇó Verbal Sentence adalah kalimat yang kata kerjanya menyatakan aktifitas dari subjek atau bisa disebut pekerjaan/tindakan seperti kata kerja eat, sleep, drink, sweep, ride, fly, ask, brush, call, dan lain-lain.

      Contoh:

      1. I walk to school
      2. We are studying English now
      3. They play football every afternoon
      4. My mother always buys vegetables

      ΓÇó Nominal Sentence adalah kalimat yang terdiri dari auxiliary verb atau kata kerja bantu yanb berupa is, am, are, was, weee, have, has, had, dan be yang tidak menyatakan aktivitas dari subjek, melainkan sebagai penghubung dan penjelas untuk menyatakan kondisi, status, dan keadaan dari complement (Adjective, Noun, Adverb of place).

      Contoh:

      1. I am a student
      2. She is a teacher
      3. He was smart student
      4. Her father has been here for one minute.
      5. We were in the class for studying, but now we are not

    • Grammar focus : Verbal and Nominal Sentence Pelajaran
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      Nominal sentence is a sentence that have not a verb, but can be an adjective, noun or adverb, then the nominal sentence needs auxiliary verb, such as is, am, are, and it is followed by adjectives/ adverb/ noun. Verbal sentence is subject followed by verb.


      Kalimat verbal dan nominal adalah pengetahuan dasar Bahasa Inggris yang wajib dipelajari. Sama halnya dengan Bahasa Indonesia, Bahasa Inggris juga memiliki tata bahasa sesuai kaidahnya. Materi ini merupakan salah satu materi pokok dalam penyusunan kosa kata yang tepat dalam Bahasa Inggris. 

      Kalimat verbal dan nominal adalah pengetahuan dasar Bahasa Inggris yang wajib dipelajari. Sama halnya dengan Bahasa Indonesia, Bahasa Inggris juga memiliki tata bahasa sesuai kaidahnya. Materi ini merupakan salah satu materi pokok dalam penyusunan kosa kata yang tepat dalam Bahasa Inggris. Sehingga bagi para pemula, mempelajari materi ini juga sangat diperlukan. Tapi apa sih kalimat verbal dan nominal itu? Nah di artikel kali ini kita akan membahas tentang kalimat verbal dan nominal.

      ΓÇó Definisi kalimat

      Kalimat adalah kata-kata yang minimal terdiri dari subyek dan predikat. Jenis kalimat sendiri ada dua yaitu kalimat verbal dan nominal.

       

      ΓÇó Verbal Sentence adalah kalimat yang kata kerjanya menyatakan aktifitas dari subjek atau bisa disebut pekerjaan/tindakan seperti kata kerja eat, sleep, drink, sweep, ride, fly, ask, brush, call, dan lain-lain.

      Contoh:

      1. I walk to school
      2. We are studying English now
      3. They play football every afternoon
      4. My mother always buys vegetables

      ΓÇó Nominal Sentence adalah kalimat yang terdiri dari auxiliary verb atau kata kerja bantu yanb berupa is, am, are, was, weee, have, has, had, dan be yang tidak menyatakan aktivitas dari subjek, melainkan sebagai penghubung dan penjelas untuk menyatakan kondisi, status, dan keadaan dari complement (Adjective, Noun, Adverb of place).

      Contoh:

      1. I am a student
      2. She is a teacher
      3. He was smart student
      4. Her father has been here for one minute.
      5. We were in the class for studying, but now we are not

    • Video about nominal and verbal sentence Halaman
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      http://

    • Discussion forum
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      I. Answer the question basedn the text of Natural Language

      1. What is Natural Language Proccessing ?

      2. What is the importance and benefit of Natural Life in any fields?

      3. Natural language processing is the driving force behind machine intelligence in many modern real-world    applications. Can you give some of the application?


      II. Vocabulary. What is the meaning of vocabulary below :

      1.  translate  2.  sofware.   3. automatically,  4. impact   5. effective   6. detection.  7. accuracy


      III. Decide the bold words based on the part of speech :

      1. The best spam detection technologies use NLP's text classification. 

      2. Google translate is an example of widely available NLP technology at work.

      3. Effective translation has to capture accurately the meaning of the input language.

      4. NLP technology digests huge volume of digital text and creates summaries. 

      5. Sentiment analysis can analyze language used in social media post and to extract emotion and attitude.

       

      IV. Making a simple sentence in verbal or nominal sentence using the words below. 

      1.  translate  2.  sofware.   3. automatically,  4. impact   5. effective   6. detection.  7. accuracy