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Natural Language Processing in Artificial Intelligence in Hindi | NLP with Demo and Examples
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{'title': 'Natural Language Processing in Artificial Intelligence in Hindi | NLP with Demo and Examples', 'heatmap': [{'end': 187.266, 'start': 161.284, 'weight': 0.785}, {'end': 406.12, 'start': 360.404, 'weight': 0.784}], 'summary': 'Delves into natural language processing (nlp) and its applications in ai, covering speech recognition by major companies and sentiment analysis in social media, including practical examples of machine translation and chatbots, while addressing challenges in nlu and nlg.', 'chapters': [{'end': 170.712, 'segs': [{'end': 33.142, 'src': 'embed', 'start': 0.309, 'weight': 1, 'content': [{'end': 2.211, 'text': 'Hello friends, welcome to Great Smasher.', 'start': 0.309, 'duration': 1.902}, {'end': 5.633, 'text': "In today's video we are going to discuss Natural Language Processing.", 'start': 2.211, 'duration': 3.422}, {'end': 12.259, 'text': 'So NLP is one of the most important and latest topic of Artificial Intelligence.', 'start': 5.633, 'duration': 6.626}, {'end': 15.801, 'text': 'So in this video we will discuss about NLP in detail with live examples.', 'start': 12.259, 'duration': 3.542}, {'end': 19.785, 'text': 'And this video will help you a lot, specially in competitive exams,', 'start': 15.801, 'duration': 3.984}, {'end': 24.869, 'text': 'or you are preparing for your college or university level exams or even preparing for interviews.', 'start': 19.785, 'duration': 5.084}, {'end': 26.75, 'text': 'So here I will give you very good facts about NLP.', 'start': 24.869, 'duration': 1.881}, {'end': 33.142, 'text': "So first of all, Let's start.", 'start': 29.353, 'duration': 3.789}], 'summary': 'Video discusses nlp with live examples, helpful for exams and interviews.', 'duration': 32.833, 'max_score': 0.309, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0309.jpg'}, {'end': 146.673, 'src': 'embed', 'start': 96.238, 'weight': 0, 'content': [{'end': 104.841, 'text': 'Means. we want the computer to replicate the same thing, Means copy the same thing, And if two computers want to talk to each other,', 'start': 96.238, 'duration': 8.603}, {'end': 114.384, 'text': 'They should talk in the same way as human beings talk Machine and human beings should talk in the same way as two human beings talk to each other.', 'start': 104.841, 'duration': 9.543}, {'end': 122.872, 'text': 'So here we want to implement the same thing with NLP, that is called Natural Language Processing.', 'start': 114.944, 'duration': 7.928}, {'end': 125.175, 'text': 'So, here I am going to tell you the applications.', 'start': 122.912, 'duration': 2.263}, {'end': 127.537, 'text': 'What are the applications of NLP?', 'start': 125.555, 'duration': 1.982}, {'end': 134.504, 'text': 'So, first of all, speech recognition is widely used and most of the research work At this time.', 'start': 127.817, 'duration': 6.687}, {'end': 141.889, 'text': 'all the major companies, major IT giants, whether it is Google or Amazon, all these people are actually working on this.', 'start': 134.504, 'duration': 7.385}, {'end': 146.673, 'text': 'In speech recognition, your biggest example is Google Assistant.', 'start': 141.909, 'duration': 4.764}], 'summary': 'Nlp aims to enable computers to mimic human communication, with widespread applications like speech recognition used by major tech companies such as google and amazon.', 'duration': 50.435, 'max_score': 96.238, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo096238.jpg'}], 'start': 0.309, 'title': 'Nlp and its applications', 'summary': 'Explains natural language processing (nlp) and its significance in ai, covering applications like speech recognition by major companies, with a focus on enabling human-like communication.', 'chapters': [{'end': 170.712, 'start': 0.309, 'title': 'Understanding nlp and its applications', 'summary': 'Explains the concept of natural language processing (nlp), its significance in artificial intelligence, and its applications such as speech recognition by major companies like google and amazon, with a focus on enabling computers to communicate in the same way as humans.', 'duration': 170.403, 'highlights': ["NLP is a significant and latest topic in Artificial Intelligence, enabling machines to communicate in natural languages like humans. NLP's importance in Artificial Intelligence.", 'Speech recognition, a key application of NLP, is widely researched and developed by major companies like Google and Amazon, with products such as Google Assistant and Siri. Significance of speech recognition in NLP and its development by major companies.', 'Describing how humans communicate through natural languages, emphasizing the need for computers to replicate the same communication process. Comparison of human and computer communication in NLP.']}], 'duration': 170.403, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0309.jpg', 'highlights': ['Speech recognition, a key application of NLP, is widely researched and developed by major companies like Google and Amazon, with products such as Google Assistant and Siri. Significance of speech recognition in NLP and its development by major companies.', "NLP is a significant and latest topic in Artificial Intelligence, enabling machines to communicate in natural languages like humans. NLP's importance in Artificial Intelligence.", 'Describing how humans communicate through natural languages, emphasizing the need for computers to replicate the same communication process. Comparison of human and computer communication in NLP.']}, {'end': 796.522, 'segs': [{'end': 242.101, 'src': 'embed', 'start': 170.712, 'weight': 1, 'content': [{'end': 176.678, 'text': 'so by interpreting and understanding that speech, it is giving you a proper and valid reply.', 'start': 170.712, 'duration': 5.966}, {'end': 178.819, 'text': 'that is called the speech decognization.', 'start': 176.678, 'duration': 2.141}, {'end': 181.421, 'text': 'Then sentiment analysis.', 'start': 179.68, 'duration': 1.741}, {'end': 185.784, 'text': "this work is also happening a lot in today's time, especially if we talk about social media.", 'start': 181.421, 'duration': 4.363}, {'end': 187.266, 'text': 'then there is Facebook.', 'start': 185.784, 'duration': 1.482}, {'end': 188.346, 'text': 'there is Twitter.', 'start': 187.266, 'duration': 1.08}, {'end': 192.91, 'text': 'whatever tweets are doing, you can analyze all these tweets.', 'start': 188.346, 'duration': 4.564}, {'end': 194.671, 'text': 'and what is the meaning of sentiments?', 'start': 192.91, 'duration': 1.761}, {'end': 198.793, 'text': 'are good or bad?', 'start': 197.773, 'duration': 1.02}, {'end': 203.595, 'text': 'like ratings are coming regarding movies, so is this movie good or bad?', 'start': 198.793, 'duration': 4.802}, {'end': 206.576, 'text': 'you can analyze this through Twitter case and check.', 'start': 203.595, 'duration': 2.981}, {'end': 216.199, 'text': 'It is election time, so in elections you can pick up tweets of any particular leader and analyze it that on whom this major focus is done.', 'start': 206.596, 'duration': 9.603}, {'end': 221.781, 'text': 'Like. I did an example of this a few days ago by using the python and tensorflow.', 'start': 216.239, 'duration': 5.542}, {'end': 224.403, 'text': 'I used this In R programming.', 'start': 221.781, 'duration': 2.622}, {'end': 229.289, 'text': 'I had analyzed it completely that how we can analyze tweets and make a word cloud of it.', 'start': 224.403, 'duration': 4.886}, {'end': 232.352, 'text': 'Through which we will know that which leader is the most focused on whom in his Twitter.', 'start': 229.309, 'duration': 3.043}, {'end': 242.101, 'text': 'So here sentiment analysis is machine translation.', 'start': 238.459, 'duration': 3.642}], 'summary': 'Speech recognition, sentiment analysis, and twitter data used for analyzing sentiments and focus on leaders during elections.', 'duration': 71.389, 'max_score': 170.712, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0170712.jpg'}, {'end': 406.12, 'src': 'heatmap', 'start': 360.404, 'weight': 0.784, 'content': [{'end': 367.427, 'text': 'So here first of all we are giving input and that input is automatic speech recognition.', 'start': 360.404, 'duration': 7.023}, {'end': 375.714, 'text': 'Speech Recognization software will pick up the speech and convert it into text to make NLU.', 'start': 369.188, 'duration': 6.526}, {'end': 381.84, 'text': 'What is NLU? Natural Language Understanding or Natural Language Interpreter.', 'start': 375.754, 'duration': 6.086}, {'end': 385.864, 'text': 'Just like I am speaking here, you are listening to all these things.', 'start': 381.86, 'duration': 4.004}, {'end': 390.228, 'text': 'As you are listening to all these things, your interpreter will also work.', 'start': 385.884, 'duration': 4.344}, {'end': 393.19, 'text': 'Here understanding is working.', 'start': 391.949, 'duration': 1.241}, {'end': 397.674, 'text': 'Means you are collecting all the words and trying to understand them.', 'start': 393.21, 'duration': 4.464}, {'end': 400.716, 'text': 'Then what you do? Natural language generation.', 'start': 397.714, 'duration': 3.002}, {'end': 406.12, 'text': 'Then on the basis of that you take decision that what reply you have to do.', 'start': 401.076, 'duration': 5.044}], 'summary': 'Automatic speech recognition processes input to enable natural language understanding and generation for decision-making.', 'duration': 45.716, 'max_score': 360.404, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0360404.jpg'}, {'end': 447.951, 'src': 'embed', 'start': 418.36, 'weight': 0, 'content': [{'end': 421.542, 'text': 'Simple, I am using Google Assistant here.', 'start': 418.36, 'duration': 3.182}, {'end': 436.012, 'text': 'Hey Google! Hi, what can I do for you? How are you? I am doing great, thanks for asking.', 'start': 422.923, 'duration': 13.089}, {'end': 444.404, 'text': "What can I help you with? What is natural language processing? Here's a summary from Wikipedia.", 'start': 436.512, 'duration': 7.892}, {'end': 447.951, 'text': 'Natural language processing is a subfield of computer science,', 'start': 444.585, 'duration': 3.366}], 'summary': 'Google assistant explains natural language processing as a subfield of computer science.', 'duration': 29.591, 'max_score': 418.36, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0418360.jpg'}, {'end': 544.199, 'src': 'embed', 'start': 514.876, 'weight': 2, 'content': [{'end': 520.202, 'text': 'No, there are many challenges here and the biggest challenge is ambiguity.', 'start': 514.876, 'duration': 5.326}, {'end': 524.526, 'text': "Meaning whatever you are understanding, whatever language you are using, let's say I am using English language.", 'start': 520.222, 'duration': 4.304}, {'end': 528.71, 'text': 'So there are many words and many types of ambiguity here.', 'start': 524.827, 'duration': 3.883}, {'end': 534.194, 'text': 'So how to remove that ambiguity? This is the biggest challenge here for the machine.', 'start': 528.73, 'duration': 5.464}, {'end': 538.076, 'text': 'So NLU software is a very big challenge here.', 'start': 534.514, 'duration': 3.562}, {'end': 544.199, 'text': 'First of all, if we talk about lexical ambiguity, then synthetic ambiguity, semantic pragmatic.', 'start': 538.096, 'duration': 6.103}], 'summary': 'The biggest challenge for nlu software is removing ambiguity in language.', 'duration': 29.323, 'max_score': 514.876, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0514876.jpg'}], 'start': 170.712, 'title': 'Nlp and sentiment analysis in social media', 'summary': 'Covers the applications of nlp, including machine translation and chatbots, in analyzing tweets and sentiment in social media, with a practical example of google assistant for natural language understanding. it also discusses challenges in nlp, such as ambiguity in language processing.', 'chapters': [{'end': 216.199, 'start': 170.712, 'title': 'Speech decognition and sentiment analysis', 'summary': 'Discusses speech decognition and sentiment analysis, highlighting their relevance in social media analysis and election focus through twitter.', 'duration': 45.487, 'highlights': ['Speech decognition is the process of interpreting and understanding speech to provide a valid reply, which is crucial for effective communication.', 'Sentiment analysis plays a significant role in social media analysis, particularly in platforms like Facebook and Twitter, enabling the analysis of tweets to determine the sentiments, such as good or bad, about movies and political leaders during elections.']}, {'end': 796.522, 'start': 216.239, 'title': 'Nlp: machine translation and chatbots', 'summary': 'Explains the applications of nlp, including machine translation for analyzing tweets, sentiment analysis, and chatbots, with a practical example of using google assistant for natural language understanding. it also delves into the challenges of nlp, such as ambiguity in lexical, syntactic, and semantic aspects of language processing.', 'duration': 580.283, 'highlights': ['Machine translation for analyzing tweets and sentiment analysis The speaker demonstrates the use of machine translation for analyzing tweets and creating word clouds to determine which leader is the most focused on in their Twitter activity.', 'Challenges in NLP, such as ambiguity in lexical, syntactic, and semantic aspects The chapter delves into the challenges of ambiguity in NLP, including lexical ambiguity, synthetic ambiguity, and semantic ambiguity, illustrating how these present hurdles for natural language understanding and generation.', "Practical example of natural language understanding using Google Assistant The speaker provides a practical example of using Google Assistant for natural language understanding, where the assistant recognizes, understands, and generates a valid reply based on the user's intention, highlighting the application of NLU in real-world scenarios."]}], 'duration': 625.81, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0170712.jpg', 'highlights': ['Practical example of natural language understanding using Google Assistant', 'Sentiment analysis in social media for analyzing tweets', 'Challenges in NLP, including ambiguity in language processing', 'Machine translation for analyzing tweets and sentiment analysis', 'Speech decognition for effective communication']}, {'end': 1014.992, 'segs': [{'end': 909.225, 'src': 'embed', 'start': 845.413, 'weight': 0, 'content': [{'end': 846.534, 'text': 'Maybe you are coming to this area.', 'start': 845.413, 'duration': 1.121}, {'end': 851.136, 'text': 'But if you are giving this language to the machine, then how will the machine interpret it?', 'start': 846.554, 'duration': 4.582}, {'end': 852.396, 'text': 'Is it coming for me??', 'start': 851.216, 'duration': 1.18}, {'end': 853.957, 'text': 'Is it coming for you??', 'start': 852.456, 'duration': 1.501}, {'end': 855.558, 'text': 'Is it coming to this area??', 'start': 853.977, 'duration': 1.581}, {'end': 856.338, 'text': 'Is it coming to roam??', 'start': 855.578, 'duration': 0.76}, {'end': 858.059, 'text': 'What is it coming to do??', 'start': 856.638, 'duration': 1.421}, {'end': 864.142, 'text': 'So, if you want to remove this thing from ambiguity, then the software of NLU is very should be intelligent.', 'start': 858.079, 'duration': 6.063}, {'end': 867.826, 'text': 'So these are actually the main challenges in NLU.', 'start': 864.182, 'duration': 3.644}, {'end': 871.51, 'text': 'Then after NLU, the next phase is NLG.', 'start': 867.886, 'duration': 3.624}, {'end': 873.572, 'text': 'That is Natural Language Generation.', 'start': 871.83, 'duration': 1.742}, {'end': 880.759, 'text': 'When we have all the understanding, like our mind has done all the understanding, now what we have to do? Now we have to reply.', 'start': 873.612, 'duration': 7.147}, {'end': 884.963, 'text': 'So the reply is What should we say to the user?', 'start': 880.799, 'duration': 4.164}, {'end': 889.267, 'text': 'So here we work on the energy, that actually, what should the user reply?', 'start': 885.204, 'duration': 4.063}, {'end': 894.292, 'text': 'Because whatever you have to reply, it should be intelligent and conversational.', 'start': 889.287, 'duration': 5.005}, {'end': 898.435, 'text': 'Means whatever you are replying, it should be intelligent and conversational.', 'start': 894.352, 'duration': 4.083}, {'end': 902.939, 'text': 'Means whatever the user has asked, you should reply on the basis of that.', 'start': 898.475, 'duration': 4.464}, {'end': 909.225, 'text': 'Like if the user has asked from Google Assistant, that Google Assistant tell me the nearby places to eat.', 'start': 902.999, 'duration': 6.226}], 'summary': 'Challenges in nlu and nlg, importance of intelligent and conversational replies to user queries.', 'duration': 63.812, 'max_score': 845.413, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0845413.jpg'}], 'start': 796.522, 'title': 'Nlu and nlg challenges and solutions', 'summary': "Delves into challenges in nlu such as language ambiguities and the need for intelligent software, followed by nlg's role in generating appropriate responses. it emphasizes the importance of intelligent and conversational replies in nlg and explains the process of natural language processing.", 'chapters': [{'end': 889.267, 'start': 796.522, 'title': 'Challenges in nlu and nlg', 'summary': 'Discusses the challenges in natural language understanding (nlu) such as dealing with ambiguities in language interpretation and the need for intelligent software, followed by the next phase of natural language generation (nlg) to generate appropriate responses to users.', 'duration': 92.745, 'highlights': ["NLU involves dealing with ambiguities in language interpretation, such as multiple meanings of phrases like 'the police are coming', requiring intelligent software to address these challenges.", 'NLG focuses on generating appropriate responses to users based on the understanding obtained during NLU, emphasizing the importance of crafting suitable replies to user queries.']}, {'end': 935.33, 'start': 889.287, 'title': 'Intelligent and conversational reply', 'summary': 'Emphasizes the importance of intelligent and conversational replies in natural language generation to ensure relevance to user queries, with the example of providing nearby places for food instead of clothing.', 'duration': 46.043, 'highlights': ['Natural Language Generation is crucial for ensuring relevant and conversational replies to user queries.', "Relevance is key in responding to user queries, with an example of providing the correct type of nearby locations based on the user's request.", 'Text and Sentence Planning are essential components of Natural Language Generation for crafting intelligent and conversational responses.']}, {'end': 1014.992, 'start': 935.67, 'title': 'Understanding natural language processing', 'summary': 'Explains the process of natural language processing, including planning the text and sentence, structuring data, and the main factors of nlu and nlg.', 'duration': 79.322, 'highlights': ['The chapter covers the process of planning the text and sentence, as well as structuring data to provide structured replies based on the whole knowledge base.', 'It emphasizes that natural language processing involves two main factors, NLU and NLG, for recognizing and generating relevant answers.', 'It explains that the corpus is the whole knowledge base used for planning text and sentence, and ultimately providing structured data for analysis and relevant responses.']}], 'duration': 218.47, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/bPpwZxasJo0/pics/bPpwZxasJo0796522.jpg', 'highlights': ['NLU involves addressing language ambiguities with intelligent software.', 'NLG focuses on generating relevant and conversational responses.', 'Text and Sentence Planning are essential for intelligent responses.', 'NLP involves NLU and NLG for recognizing and generating answers.', 'Relevance is crucial in responding to user queries for effective communication.']}], 'highlights': ['Speech recognition, a key application of NLP, is widely researched and developed by major companies like Google and Amazon, with products such as Google Assistant and Siri. Significance of speech recognition in NLP and its development by major companies.', "NLP is a significant and latest topic in Artificial Intelligence, enabling machines to communicate in natural languages like humans. NLP's importance in Artificial Intelligence.", 'Describing how humans communicate through natural languages, emphasizing the need for computers to replicate the same communication process. Comparison of human and computer communication in NLP.', 'Practical example of natural language understanding using Google Assistant', 'Sentiment analysis in social media for analyzing tweets', 'Challenges in NLP, including ambiguity in language processing', 'Machine translation for analyzing tweets and sentiment analysis', 'Speech decognition for effective communication', 'NLU involves addressing language ambiguities with intelligent software.', 'NLG focuses on generating relevant and conversational responses.', 'Text and Sentence Planning are essential for intelligent responses.', 'NLP involves NLU and NLG for recognizing and generating answers.', 'Relevance is crucial in responding to user queries for effective communication.']}