�ݺ�ߣshows by User: nithishrw

�ݺ�ߣshows by User: nithishrw / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: nithishrw / Sun, 09 Mar 2025 16:29:23 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: nithishrw Evaluating the Effectiveness of RAG in Real World Applications /slideshow/evaluating-the-effectiveness-of-rag-in-real-world-applications/276463318 scale22xevaluatingeffectivenessofraginrealworldapplications-250309162923-d95d2bc0
This talk was delieved at SCaLE held in Pasadena, Los Angeles, California on March 7th 2025 (https://www.socallinuxexpo.org/scale/22x/presentations/evaluating-effectiveness-retrieval-augmented-generation-rag-real-world). Abstract: With the rise of large language models (LLMs) enhanced by retrieval augmented generation (RAG), it has become essential to develop rigorous evaluation methodologies to assess their effectiveness across diverse use cases. RAG combines a model's generative capabilities with information retrieval, allowing for contextually relevant responses grounded in up-to-date, factual knowledge. This talk will focus on the unique challenges and best practices for evaluating RAG applications covering quantitative metrics (e.g., accuracy, relevance, etc). The audience will gain insights into how to choose the right evaluation framework, balance retrieval precision with generation creativity, and interpret evaluation results to enhance RAG systems' deployment success in settings like customer support, content generation, research assistance, and more. Key Takeaways: - Understand core metrics and methods for evaluating RAG applications. - Explore domain-specific evaluation needs and limitations. - Learn practical techniques for improving RAG application performance based on evaluation insights.]]>
This talk was delieved at SCaLE held in Pasadena, Los Angeles, California on March 7th 2025 (https://www.socallinuxexpo.org/scale/22x/presentations/evaluating-effectiveness-retrieval-augmented-generation-rag-real-world). Abstract: With the rise of large language models (LLMs) enhanced by retrieval augmented generation (RAG), it has become essential to develop rigorous evaluation methodologies to assess their effectiveness across diverse use cases. RAG combines a model's generative capabilities with information retrieval, allowing for contextually relevant responses grounded in up-to-date, factual knowledge. This talk will focus on the unique challenges and best practices for evaluating RAG applications covering quantitative metrics (e.g., accuracy, relevance, etc). The audience will gain insights into how to choose the right evaluation framework, balance retrieval precision with generation creativity, and interpret evaluation results to enhance RAG systems' deployment success in settings like customer support, content generation, research assistance, and more. Key Takeaways: - Understand core metrics and methods for evaluating RAG applications. - Explore domain-specific evaluation needs and limitations. - Learn practical techniques for improving RAG application performance based on evaluation insights.]]> Sun, 09 Mar 2025 16:29:23 GMT /slideshow/evaluating-the-effectiveness-of-rag-in-real-world-applications/276463318 nithishrw@slideshare.net(nithishrw) Evaluating the Effectiveness of RAG in Real World Applications nithishrw This talk was delieved at SCaLE held in Pasadena, Los Angeles, California on March 7th 2025 (https://www.socallinuxexpo.org/scale/22x/presentations/evaluating-effectiveness-retrieval-augmented-generation-rag-real-world). Abstract: With the rise of large language models (LLMs) enhanced by retrieval augmented generation (RAG), it has become essential to develop rigorous evaluation methodologies to assess their effectiveness across diverse use cases. RAG combines a model's generative capabilities with information retrieval, allowing for contextually relevant responses grounded in up-to-date, factual knowledge. This talk will focus on the unique challenges and best practices for evaluating RAG applications covering quantitative metrics (e.g., accuracy, relevance, etc). The audience will gain insights into how to choose the right evaluation framework, balance retrieval precision with generation creativity, and interpret evaluation results to enhance RAG systems' deployment success in settings like customer support, content generation, research assistance, and more. Key Takeaways: - Understand core metrics and methods for evaluating RAG applications. - Explore domain-specific evaluation needs and limitations. - Learn practical techniques for improving RAG application performance based on evaluation insights. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/scale22xevaluatingeffectivenessofraginrealworldapplications-250309162923-d95d2bc0-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk was delieved at SCaLE held in Pasadena, Los Angeles, California on March 7th 2025 (https://www.socallinuxexpo.org/scale/22x/presentations/evaluating-effectiveness-retrieval-augmented-generation-rag-real-world). Abstract: With the rise of large language models (LLMs) enhanced by retrieval augmented generation (RAG), it has become essential to develop rigorous evaluation methodologies to assess their effectiveness across diverse use cases. RAG combines a model's generative capabilities with information retrieval, allowing for contextually relevant responses grounded in up-to-date, factual knowledge. This talk will focus on the unique challenges and best practices for evaluating RAG applications covering quantitative metrics (e.g., accuracy, relevance, etc). The audience will gain insights into how to choose the right evaluation framework, balance retrieval precision with generation creativity, and interpret evaluation results to enhance RAG systems' deployment success in settings like customer support, content generation, research assistance, and more. Key Takeaways: - Understand core metrics and methods for evaluating RAG applications. - Explore domain-specific evaluation needs and limitations. - Learn practical techniques for improving RAG application performance based on evaluation insights.

Evaluating the Effectiveness of RAG in Real World Applications from Nithish Raghunandanan

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0 AI_Photo_Generation_with_Python_A_Developer's_Guide.pdf /slideshow/ai_photo_generation_with_python_a_developer-s_guide-pdf/275128158 pyconwebaiphotogenerationwithpythonadevelopersguide-250125103700-9b44208e
This talk was delivered at PyConWeb 2025 (https://www.pyconweb.com/). The line between traditional photography and AI-generated imagery is becoming increasingly blurred, thanks to advancements in AI technologies like generative adversarial networks (GANs) and diffusion models. This talk will focus on building a Python application that uses AI to generate realistic photos. The talk will provide a practical roadmap for turning an idea into a fully functional application. Attendees will gain insights into the challenges of ensuring photo realism, optimizing performance, and handling ethical considerations like authenticity and copyright. Key Takeaways: - Understand the core technologies behind AI-driven photo generation. - Learn the end-to-end process of developing an AI-powered application. - Explore strategies for ensuring realism, usability, and ethical compliance.]]>
This talk was delivered at PyConWeb 2025 (https://www.pyconweb.com/). The line between traditional photography and AI-generated imagery is becoming increasingly blurred, thanks to advancements in AI technologies like generative adversarial networks (GANs) and diffusion models. This talk will focus on building a Python application that uses AI to generate realistic photos. The talk will provide a practical roadmap for turning an idea into a fully functional application. Attendees will gain insights into the challenges of ensuring photo realism, optimizing performance, and handling ethical considerations like authenticity and copyright. Key Takeaways: - Understand the core technologies behind AI-driven photo generation. - Learn the end-to-end process of developing an AI-powered application. - Explore strategies for ensuring realism, usability, and ethical compliance.]]> Sat, 25 Jan 2025 10:37:00 GMT /slideshow/ai_photo_generation_with_python_a_developer-s_guide-pdf/275128158 nithishrw@slideshare.net(nithishrw) AI_Photo_Generation_with_Python_A_Developer's_Guide.pdf nithishrw This talk was delivered at PyConWeb 2025 (https://www.pyconweb.com/). The line between traditional photography and AI-generated imagery is becoming increasingly blurred, thanks to advancements in AI technologies like generative adversarial networks (GANs) and diffusion models. This talk will focus on building a Python application that uses AI to generate realistic photos. The talk will provide a practical roadmap for turning an idea into a fully functional application. Attendees will gain insights into the challenges of ensuring photo realism, optimizing performance, and handling ethical considerations like authenticity and copyright. Key Takeaways: - Understand the core technologies behind AI-driven photo generation. - Learn the end-to-end process of developing an AI-powered application. - Explore strategies for ensuring realism, usability, and ethical compliance. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pyconwebaiphotogenerationwithpythonadevelopersguide-250125103700-9b44208e-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk was delivered at PyConWeb 2025 (https://www.pyconweb.com/). The line between traditional photography and AI-generated imagery is becoming increasingly blurred, thanks to advancements in AI technologies like generative adversarial networks (GANs) and diffusion models. This talk will focus on building a Python application that uses AI to generate realistic photos. The talk will provide a practical roadmap for turning an idea into a fully functional application. Attendees will gain insights into the challenges of ensuring photo realism, optimizing performance, and handling ethical considerations like authenticity and copyright. Key Takeaways: - Understand the core technologies behind AI-driven photo generation. - Learn the end-to-end process of developing an AI-powered application. - Explore strategies for ensuring realism, usability, and ethical compliance.

AI_Photo_Generation_with_Python_A_Developer's_Guide.pdf from Nithish Raghunandanan

]]> 86 0 https://cdn.slidesharecdn.com/ss_thumbnails/pyconwebaiphotogenerationwithpythonadevelopersguide-250125103700-9b44208e-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Next Generation Apps: Enhancing User Experience with LLMs.pdf /slideshow/next-generation-apps-enhancing-user-experience-with-llms-pdf/272530625 pyconptnextgenappsenhancinguserexperiencewithllms1-241018141013-fc816af3
This talk was delivered at PyCon Portugal 2024 (https://2024.pycon.pt/home/). Large Language Models(LLMs) are good at reasoning based on their knowledge. This talk explores how you can use the power of LLMs to add intelligence like coding assistants, text-to-sequel, etc to existing applications. One of the simplest ways to start adding intelligence is by using an LLM with fine-tuned prompts. You can find the answers to questions like: - What are some of the things that you need to consider while prompt engineering? - What are the limits of prompt engineering? After finding out the limits of prompt engineering, let us understand how to augment the knowledge of the LLM using vector databases. You can learn things like: - Ingesting the data into the vector databases. - Considerations in data ingestion to improve the LLM performance. We will also cover the concept of AI agents that given a set of capabilities or tools can figure out how to use them where relevant in an intelligent fashion. You can learn - How do agents work? - Where are they useful? After this talk, you will learn how to add intelligence to existing applications with the help of the ever-popular LLMs using open-source frameworks.]]>
This talk was delivered at PyCon Portugal 2024 (https://2024.pycon.pt/home/). Large Language Models(LLMs) are good at reasoning based on their knowledge. This talk explores how you can use the power of LLMs to add intelligence like coding assistants, text-to-sequel, etc to existing applications. One of the simplest ways to start adding intelligence is by using an LLM with fine-tuned prompts. You can find the answers to questions like: - What are some of the things that you need to consider while prompt engineering? - What are the limits of prompt engineering? After finding out the limits of prompt engineering, let us understand how to augment the knowledge of the LLM using vector databases. You can learn things like: - Ingesting the data into the vector databases. - Considerations in data ingestion to improve the LLM performance. We will also cover the concept of AI agents that given a set of capabilities or tools can figure out how to use them where relevant in an intelligent fashion. You can learn - How do agents work? - Where are they useful? After this talk, you will learn how to add intelligence to existing applications with the help of the ever-popular LLMs using open-source frameworks.]]> Fri, 18 Oct 2024 14:10:12 GMT /slideshow/next-generation-apps-enhancing-user-experience-with-llms-pdf/272530625 nithishrw@slideshare.net(nithishrw) Next Generation Apps: Enhancing User Experience with LLMs.pdf nithishrw This talk was delivered at PyCon Portugal 2024 (https://2024.pycon.pt/home/). Large Language Models(LLMs) are good at reasoning based on their knowledge. This talk explores how you can use the power of LLMs to add intelligence like coding assistants, text-to-sequel, etc to existing applications. One of the simplest ways to start adding intelligence is by using an LLM with fine-tuned prompts. You can find the answers to questions like: - What are some of the things that you need to consider while prompt engineering? - What are the limits of prompt engineering? After finding out the limits of prompt engineering, let us understand how to augment the knowledge of the LLM using vector databases. You can learn things like: - Ingesting the data into the vector databases. - Considerations in data ingestion to improve the LLM performance. We will also cover the concept of AI agents that given a set of capabilities or tools can figure out how to use them where relevant in an intelligent fashion. You can learn - How do agents work? - Where are they useful? After this talk, you will learn how to add intelligence to existing applications with the help of the ever-popular LLMs using open-source frameworks. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pyconptnextgenappsenhancinguserexperiencewithllms1-241018141013-fc816af3-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk was delivered at PyCon Portugal 2024 (https://2024.pycon.pt/home/). Large Language Models(LLMs) are good at reasoning based on their knowledge. This talk explores how you can use the power of LLMs to add intelligence like coding assistants, text-to-sequel, etc to existing applications. One of the simplest ways to start adding intelligence is by using an LLM with fine-tuned prompts. You can find the answers to questions like: - What are some of the things that you need to consider while prompt engineering? - What are the limits of prompt engineering? After finding out the limits of prompt engineering, let us understand how to augment the knowledge of the LLM using vector databases. You can learn things like: - Ingesting the data into the vector databases. - Considerations in data ingestion to improve the LLM performance. We will also cover the concept of AI agents that given a set of capabilities or tools can figure out how to use them where relevant in an intelligent fashion. You can learn - How do agents work? - Where are they useful? After this talk, you will learn how to add intelligence to existing applications with the help of the ever-popular LLMs using open-source frameworks.

Next Generation Apps: Enhancing User Experience with LLMs.pdf from Nithish Raghunandanan

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0 Select ML from Databases.pdf /slideshow/select-ml-from-databasespdf/251866385 pyconltselectmlfromdatabases1-220527073800-d2a82a28
This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at PyCon Lithuania 2022 held in Vilnius, Lithuania on May 26, 2022 (https://pycon.lt/)]]>
This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at PyCon Lithuania 2022 held in Vilnius, Lithuania on May 26, 2022 (https://pycon.lt/)]]> Fri, 27 May 2022 07:38:00 GMT /slideshow/select-ml-from-databasespdf/251866385 nithishrw@slideshare.net(nithishrw) Select ML from Databases.pdf nithishrw This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at PyCon Lithuania 2022 held in Vilnius, Lithuania on May 26, 2022 (https://pycon.lt/) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pyconltselectmlfromdatabases1-220527073800-d2a82a28-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at PyCon Lithuania 2022 held in Vilnius, Lithuania on May 26, 2022 (https://pycon.lt/)

Select ML from Databases.pdf from Nithish Raghunandanan

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0 Select ML from Databases /slideshow/select-ml-from-databases-251866381/251866381 selectmlfromdatabasespdf-220527073718-29d7e0e8
This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at Pyjamas 2021 held virtually on December 4 2021 (https://pyjamas.live/schedule/#session-8)]]>
This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at Pyjamas 2021 held virtually on December 4 2021 (https://pyjamas.live/schedule/#session-8)]]> Fri, 27 May 2022 07:37:18 GMT /slideshow/select-ml-from-databases-251866381/251866381 nithishrw@slideshare.net(nithishrw) Select ML from Databases nithishrw This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at Pyjamas 2021 held virtually on December 4 2021 (https://pyjamas.live/schedule/#session-8) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/selectmlfromdatabasespdf-220527073718-29d7e0e8-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk introduces a new workflow for building your machine learning models using the capabilities of modern databases that support machine learning use cases natively. There is an overview of how machine learning models are being created today to how they could look in the near future. This talk was given at Pyjamas 2021 held virtually on December 4 2021 (https://pyjamas.live/schedule/#session-8)

Select ML from Databases from Nithish Raghunandanan

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0 Virtual tourism in covid times /slideshow/virtual-tourism-in-covid-times/249876292 virtualtourismincovidtimes-210728121835
The talk covers how you can visualize your Google location history using Streamlit. It covers how you can get the data, cleanse it, augment it using images and finally visualize it using Python without using any Javascript libraries. This talk was given at EuroPython 2021 (https://ep2021.europython.eu/talks/4NTyz92-virtual-tourism-in-covid-times/)]]>
The talk covers how you can visualize your Google location history using Streamlit. It covers how you can get the data, cleanse it, augment it using images and finally visualize it using Python without using any Javascript libraries. This talk was given at EuroPython 2021 (https://ep2021.europython.eu/talks/4NTyz92-virtual-tourism-in-covid-times/)]]> Wed, 28 Jul 2021 12:18:34 GMT /slideshow/virtual-tourism-in-covid-times/249876292 nithishrw@slideshare.net(nithishrw) Virtual tourism in covid times nithishrw The talk covers how you can visualize your Google location history using Streamlit. It covers how you can get the data, cleanse it, augment it using images and finally visualize it using Python without using any Javascript libraries. This talk was given at EuroPython 2021 (https://ep2021.europython.eu/talks/4NTyz92-virtual-tourism-in-covid-times/) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/virtualtourismincovidtimes-210728121835-thumbnail.jpg?width=120&height=120&fit=bounds" /> The talk covers how you can visualize your Google location history using Streamlit. It covers how you can get the data, cleanse it, augment it using images and finally visualize it using Python without using any Javascript libraries. This talk was given at EuroPython 2021 (https://ep2021.europython.eu/talks/4NTyz92-virtual-tourism-in-covid-times/)

Virtual tourism in covid times from Nithish Raghunandanan

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0 Life of a data engineer /slideshow/life-of-a-data-engineer/245257318 lifeofadataengineer-210329093535
This talk covers the role of a Data Engineer in the industry, including why companies need them and what they do on a day to day basis. The talk will include an overview of some of the common skills required for this role. A few example projects from the industry are also described briefly. This talk was given to the students of Federal Institute of Science and Technology, India on 29th March 2021.]]>
This talk covers the role of a Data Engineer in the industry, including why companies need them and what they do on a day to day basis. The talk will include an overview of some of the common skills required for this role. A few example projects from the industry are also described briefly. This talk was given to the students of Federal Institute of Science and Technology, India on 29th March 2021.]]> Mon, 29 Mar 2021 09:35:35 GMT /slideshow/life-of-a-data-engineer/245257318 nithishrw@slideshare.net(nithishrw) Life of a data engineer nithishrw This talk covers the role of a Data Engineer in the industry, including why companies need them and what they do on a day to day basis. The talk will include an overview of some of the common skills required for this role. A few example projects from the industry are also described briefly. This talk was given to the students of Federal Institute of Science and Technology, India on 29th March 2021. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lifeofadataengineer-210329093535-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk covers the role of a Data Engineer in the industry, including why companies need them and what they do on a day to day basis. The talk will include an overview of some of the common skills required for this role. A few example projects from the industry are also described briefly. This talk was given to the students of Federal Institute of Science and Technology, India on 29th March 2021.

Life of a data engineer from Nithish Raghunandanan

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0 Creating data apps using Streamlit in Python /slideshow/creating-data-apps-in-python/239811004 creatingdataappsinpython-201206164801
Have you always wanted a flexible & interactive visualization that is easy for others to work with without handling all the Javascript libraries? Or do you want to build a user interface for your Machine Learning Model? This talk has you covered with building data apps in Python using Streamlit. It was presented at the Pyjamas Conference held virtualy across December 5th & 6th, 2020 (https://pyjamas.live/)]]>
Have you always wanted a flexible & interactive visualization that is easy for others to work with without handling all the Javascript libraries? Or do you want to build a user interface for your Machine Learning Model? This talk has you covered with building data apps in Python using Streamlit. It was presented at the Pyjamas Conference held virtualy across December 5th & 6th, 2020 (https://pyjamas.live/)]]> Sun, 06 Dec 2020 16:48:01 GMT /slideshow/creating-data-apps-in-python/239811004 nithishrw@slideshare.net(nithishrw) Creating data apps using Streamlit in Python nithishrw Have you always wanted a flexible & interactive visualization that is easy for others to work with without handling all the Javascript libraries? Or do you want to build a user interface for your Machine Learning Model? This talk has you covered with building data apps in Python using Streamlit. It was presented at the Pyjamas Conference held virtualy across December 5th & 6th, 2020 (https://pyjamas.live/) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/creatingdataappsinpython-201206164801-thumbnail.jpg?width=120&height=120&fit=bounds" /> Have you always wanted a flexible & interactive visualization that is easy for others to work with without handling all the Javascript libraries? Or do you want to build a user interface for your Machine Learning Model? This talk has you covered with building data apps in Python using Streamlit. It was presented at the Pyjamas Conference held virtualy across December 5th & 6th, 2020 (https://pyjamas.live/)

Creating data apps using Streamlit in Python from Nithish Raghunandanan

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0 Learnings from Organizing Internal Hackathons /slideshow/learnings-from-organizing-internal-hackathons-237409387/237409387 learningsfromorganizinginternalhackathons-200730155255
The talk covers some of my learnings & observations from organizing internal hackathons at a consulting company. This talk was given in one of the unconference sessions at DevRelCon Earth 2020 (https://2020.devrel.net/) on 30th July 2020. ]]>
The talk covers some of my learnings & observations from organizing internal hackathons at a consulting company. This talk was given in one of the unconference sessions at DevRelCon Earth 2020 (https://2020.devrel.net/) on 30th July 2020. ]]> Thu, 30 Jul 2020 15:52:55 GMT /slideshow/learnings-from-organizing-internal-hackathons-237409387/237409387 nithishrw@slideshare.net(nithishrw) Learnings from Organizing Internal Hackathons nithishrw The talk covers some of my learnings & observations from organizing internal hackathons at a consulting company. This talk was given in one of the unconference sessions at DevRelCon Earth 2020 (https://2020.devrel.net/) on 30th July 2020. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learningsfromorganizinginternalhackathons-200730155255-thumbnail.jpg?width=120&height=120&fit=bounds" /> The talk covers some of my learnings & observations from organizing internal hackathons at a consulting company. This talk was given in one of the unconference sessions at DevRelCon Earth 2020 (https://2020.devrel.net/) on 30th July 2020.

Learnings from Organizing Internal Hackathons from Nithish Raghunandanan

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0 Learnings from Organizing an Internal Hackathon /slideshow/learnings-from-organizing-an-internal-hackathon/156422640 ki-hacks-190719081921
The talk discusses what goes behind the scenes of an internal hackathon from the motivation, processes & the outcomes from it. The talk was given at the Developer Relations Munich Meetup (https://www.meetup.com/Dev-Rel-Munich/events/262892022/)]]>
The talk discusses what goes behind the scenes of an internal hackathon from the motivation, processes & the outcomes from it. The talk was given at the Developer Relations Munich Meetup (https://www.meetup.com/Dev-Rel-Munich/events/262892022/)]]> Fri, 19 Jul 2019 08:19:21 GMT /slideshow/learnings-from-organizing-an-internal-hackathon/156422640 nithishrw@slideshare.net(nithishrw) Learnings from Organizing an Internal Hackathon nithishrw The talk discusses what goes behind the scenes of an internal hackathon from the motivation, processes & the outcomes from it. The talk was given at the Developer Relations Munich Meetup (https://www.meetup.com/Dev-Rel-Munich/events/262892022/) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ki-hacks-190719081921-thumbnail.jpg?width=120&height=120&fit=bounds" /> The talk discusses what goes behind the scenes of an internal hackathon from the motivation, processes & the outcomes from it. The talk was given at the Developer Relations Munich Meetup (https://www.meetup.com/Dev-Rel-Munich/events/262892022/)

Learnings from Organizing an Internal Hackathon from Nithish Raghunandanan

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0 Pecha kucha Talk on web scraping /slideshow/pecha-kucha-talk-on-web-scraping/116904120 pechakuchatalkwebscraping-180927145913
The story of how I found my home in Munich with the help of web scraping]]>
The story of how I found my home in Munich with the help of web scraping]]> Thu, 27 Sep 2018 14:59:12 GMT /slideshow/pecha-kucha-talk-on-web-scraping/116904120 nithishrw@slideshare.net(nithishrw) Pecha kucha Talk on web scraping nithishrw The story of how I found my home in Munich with the help of web scraping <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pechakuchatalkwebscraping-180927145913-thumbnail.jpg?width=120&height=120&fit=bounds" /> The story of how I found my home in Munich with the help of web scraping

Pecha kucha Talk on web scraping from Nithish Raghunandanan

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0 Hodor: Solving Everyday Problems with Tech /slideshow/hodor-solving-everyday-problems-with-tech/101286466 hodormeetuptalk-180608083323
How to solve everyday problems using technology? A brief description of how we open our office door from Slack.]]>
How to solve everyday problems using technology? A brief description of how we open our office door from Slack.]]> Fri, 08 Jun 2018 08:33:23 GMT /slideshow/hodor-solving-everyday-problems-with-tech/101286466 nithishrw@slideshare.net(nithishrw) Hodor: Solving Everyday Problems with Tech nithishrw How to solve everyday problems using technology? A brief description of how we open our office door from Slack. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hodormeetuptalk-180608083323-thumbnail.jpg?width=120&height=120&fit=bounds" /> How to solve everyday problems using technology? A brief description of how we open our office door from Slack.

Hodor: Solving Everyday Problems with Tech from Nithish Raghunandanan

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0 Tutorial on Web Scraping in Python /slideshow/tutorial-on-web-scraping-in-python/81775676 scrapingtheweb-171108214352
Tutorial on Scraping Data from the Web with Python using Scrapy and BeautifulSoup at PyData Munich held at Burda Bootcamp.]]>
Tutorial on Scraping Data from the Web with Python using Scrapy and BeautifulSoup at PyData Munich held at Burda Bootcamp.]]> Wed, 08 Nov 2017 21:43:52 GMT /slideshow/tutorial-on-web-scraping-in-python/81775676 nithishrw@slideshare.net(nithishrw) Tutorial on Web Scraping in Python nithishrw Tutorial on Scraping Data from the Web with Python using Scrapy and BeautifulSoup at PyData Munich held at Burda Bootcamp. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/scrapingtheweb-171108214352-thumbnail.jpg?width=120&height=120&fit=bounds" /> Tutorial on Scraping Data from the Web with Python using Scrapy and BeautifulSoup at PyData Munich held at Burda Bootcamp.

Tutorial on Web Scraping in Python from Nithish Raghunandanan

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0 https://cdn.slidesharecdn.com/profile-photo-nithishrw-48x48.jpg?cb=1737801389 I am Nithish, an Engineer with a background in diverse areas including Software Engineering, Dev Ops, Developer Relations, Data Engineering, Lean Startups, Design Thinking, Machine Learning & Building Communities. I love to build products that solve real problems in short spans of time. In my free time, I like to read, hack stuff, attend local tech events, travel & follow Olympic sports. https://www.nithishr.com https://cdn.slidesharecdn.com/ss_thumbnails/scale22xevaluatingeffectivenessofraginrealworldapplications-250309162923-d95d2bc0-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/evaluating-the-effectiveness-of-rag-in-real-world-applications/276463318 Evaluating the Effecti... https://cdn.slidesharecdn.com/ss_thumbnails/pyconwebaiphotogenerationwithpythonadevelopersguide-250125103700-9b44208e-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/ai_photo_generation_with_python_a_developer-s_guide-pdf/275128158 AI_Photo_Generation_wi... https://cdn.slidesharecdn.com/ss_thumbnails/pyconptnextgenappsenhancinguserexperiencewithllms1-241018141013-fc816af3-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/next-generation-apps-enhancing-user-experience-with-llms-pdf/272530625 Next Generation Apps: ...