Data Professor
Data Science Podcast with @misraturp
updated
There's lots to customize here and make your own voice agent, watch the video and find out how!
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β³ Timestamp
0:00 Introduction
0:27 Repo overview
1:00 Project overview
3:00 Code walkthrough
13:37 Voice agent demo
17:39 Tips for voice agent customization
19:49 Setting up the project
27:22 Conclusion
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π Code github.com/landing-ai/landingai-python/blob/main/examples/license-plate-ocr-notebook/license_plate_ocr.ipynb
π Docs landing-ai.github.io/landingai-python
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β¨ Conference website https://www.scbioinfo.cl/reunion-anual-2024
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To do this, we're leveraging the following AI tech stack:
- AssemblyAI for accurate speech recognition using their new Universal 2 model.
Get $50 free API credit assemblyai.com/?utm_source=youtube&utm_medium=influencer&utm_campaign=dataprofessor_USM2
- Anthropic's Claude as the LLM anthropic.com
- Eleven Labs for natural-sounding speech synthesis in up to 32 languages elevenlabs.io
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ChEMBL ebi.ac.uk/chembl
π Papers
- Exploring the chemical space of aromatase inhibitors link.springer.com/article/10.1007/s11030-013-9462-x
- Origin of aromatase inhibitory activity via proteochemometric modeling peerj.com/articles/1979
- Molecular docking of aromatase inhibitors mdpi.com/1420-3049/16/5/3597
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What are timestamps? You can think of it as a table of contents for a video that will allow you to hop around the video to specific topics of interest.
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β³ Timestamps
0:00 Introduction
1:11 Setting Up the Development Environment
4:15 Audio Processing and Transcription
5:21 Generating Topics and Timestamps
8:24 Conclusion
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β° Time stamps
0:00 Introduction and guest background
5:38 Python learning experiences and evolution of development tools
11:07 Python community in Latin America and Spanish-speaking countries
17:30 Impact of AI on coding
25:55 Evolution of programming abstraction and the role of AI
32:05 Advice for Python learners and improving public speaking skills
37:04 Choosing a programming language and factors to consider
41:30 Conclusion
* Time stamp generated using AssemblyAI assemblyai.com/?utm_source=youtube&utm_medium=influencer&utm_campaign=dataprofessor_aug24
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βοΈ Giveaway details
- NVIDIA is giving away free course / certification to lucky winners
- To enter the giveaway participants must take a FREE self paced course.
- Afterwards fill out the Google form to submit a photo for proof that you've taken the course.
- Fill out this form https://forms.gle/jfekUmdyDp1ux23Q7
π€ NVIDIA course/certification
Master in-demand skills in AI, data science, accelerated computing, and more through NVIDIA's specialized training and certification, enhancing your professional knowledge and industry recognition.
- Generative AI learning path nvda.ws/3ZeCWCV
- NVIDIA Certification nvda.ws/3Z9nkRb
β° Timeline
0:00 Introduction
3:44 Exploring NVIDIA certification
15:00 Exploring NVIDIA course
17:58 Summary
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In a nutshell, the general workflow includes:
1. Extracting and downloading the audio from a YouTube video
2. Transcribing the audio into text form
3. Answer questions about the video using LeMUR from AssemblyAI, where under the hood Anthropic's Claude 3.5 Sonnet is used as the large language model.
AssemblyAI has generously provided API credits for the tutorial and has agreed to provide $50 free credits to viewers of this video:
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π Vizzu vizzu.io
π ipyvizzu ipyvizzu.vizzuhq.com
β° Timeline
0:00 Introduction
0:21 Peter's journey in Tech
6:24 What is Vizzu?
7:41 What challenges is Vizzu solving?
10:23 Taking a look at Vizzu
38:24 Most difficult chart to create
40:43 Recreating Hans Rosling animated chart
41:58 Data visualization for content creators
44:18 Data visualization for academia and researchers
48:20 Different charts that Vizzu supports
50:21 Vizzu for beginners to data
54:16 Elements of a Vizzu chart
56:30 Contributing to Vizzu Open Source
59:39 Future of Vizzu
1:01:28 Typical day in the life as a CEO
1:03:46 Getting started with Vizzu
1:06:06 Conclusion
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In this video, Cheuk shares her advice to newcomers to Python and Tech.
In this video, Cheuk shares her tips on learning Python.
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δ· Code statisticsglobe.com/data-manipulation-visualization-r-tidyverse
π Course statisticsglobe.com/online-course-data-manipulation-r-dplyr-tidyverse
πΊ Joachim's YouTube channel @StatisticsGlobe
-----
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In this video, Cheuk shares her journey on how she got started in Python and break into Tech.
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#datascience #machinelearning #python #pycon #dataprofessor
π Connect with Nick linkedin.com/in/uzoma-nicholas-muoh-58284960
This video was filmed at @PyConUS in Pittsburgh, Pennsylvania in May 2024.
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π Code github.com/dataprofessor/llama2
Note: Look for Llama2.ipynb and llama2-local.py
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πΉοΈ Try the State of LLM Apps https://state-of-llm.streamlit.app/
Learn more insights and get started on your LLM app building journey by attending BUILD, a free virtual conference Dec 5-6, 2023. Join 35k developers to explore apps, data pipelines, and ML workflows in the age of LLMs and generative AI.
βοΈ Register for BUILD: snowflake.com/build/americas/?utm_source=streamlit&utm_medium=dataprofessor&utm_campaign=build-summit-streamlit
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Tyler is a Senior Data Scientist at Snowflake Inc. working on the Streamlit Open Source team.
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π¦ Twitter twitter.com/tylerjrichards
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#datascience #machinelearning #dataprofessor
In a nutshell, you'll build an LLM app using one or more of the following LLM technology from these partners:
- LangChain
- AssemblyAI
- Weaviate
- LlamaIndex
- Clarifai
π Go to the LLM Hackathon streamlit.io/community/llm-hackathon-2023?utm_campaign=2023-Q3%20LLM%20Hackathon&utm_medium=social&utm_source=youtube&utm_content=dataprofessor
Here's a quick summary:
π When? September 5-19, 2023
π Prizes! Lots of cool swags and prizes!
πΊοΈ Where? Virtual Hackathon
_________________
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Currently the LLM model provided on Hugging Chat includes: meta-llama/Llama-2-70b-chat-hf and OpenAssistant/oasst-sft-6-llama-30b.
π Code github.com/dataprofessor/hugchat
π€ Hugging Chat huggingface.co/chat
π HugChat Python library pypi.org/project/hugchat
π Blog - How to build an LLM-powered ChatBot with Streamlit blog.streamlit.io/how-to-build-an-llm-powered-chatbot-with-streamlit
πΉοΈ App demo https://hugchat.streamlit.app/
π App repo github.com/dataprofessor/hugchat
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Features of GitHub Codespaces github.com/features/codespaces
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π Watch this next - Podcast with Mito founders - youtube.com/watch?v=kzB9QLYdnC0
π Read this next - Blog on Mito as a powerful spreadsheet in Streamlit - blog.streamlit.io/data-analysis-with-mito-a-powerful-spreadsheet-in-streamlit
π οΈ Mito Docs on Creating a Mito app using @streamlitofficial bit.ly/3KBkexk
βοΈ Deploy to Streamlit Community Cloud streamlit.io/cloud
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βοΈ Watch this video on how to build a Llama 2 chatbot app using @streamlitofficial youtu.be/J8TgKxomS2g
π Jupyter notebook github.com/dataprofessor/llama2
π οΈ Tutorial blog on building the Llama 2 chatbot blog.streamlit.io/how-to-build-a-llama-2-chatbot
π Llama 2 release note ai.meta.com/llama
π¦ Llama 2 model (7B) on Replicate replicate.com/a16z-infra/llama-2-7b-chat
π¦ Llama 2 model (13B) on Replicate replicate.com/a16z-infra/llama-2-13b-chat
π¦ Llama 2 model (70B) on Replicate replicate.com/replicate/llama-2-70b-chat
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π Watch the full video youtu.be/MD9aAMMyZCQ
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In this video, Jake introduces Mito AI where users can access ChatGPT from inside their Python environment. The user can have Mito AI complete tasks or answer questions with the data, and each edit will be reflected in the Mito interface, as well as generate the equivalent Python code. Mito AI allows the user to generate code with an LLM, and validate that the LLM was correct by seeing their data change in the spreadsheet in real time. Mito will highlight all the changes that the LLM makes, so the user can easily validate them.
π Mito AI Product Hunt Page producthunt.com/posts/mito-ai
π Read more about Mito AI docs.trymito.io/how-to/mito-ai
βοΈ Mito install instructions docs.trymito.io/getting-started/installing-mito
Note: This is not a sponsored video.
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π Watch the full version of this video youtu.be/MD9aAMMyZCQ
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Timeline
0:00 Introduction
0:32 Step 1 Identifying the problem
2:28 Step 2 Choose a programming language
3:25 Step 3 Build projects
5:26 Step 4 Tools of the trade
9:35 Bonus 1 - Books
10:52 Bonus 2 - Getting unstuck
12:00 Bonus 3 - Content creation
12:58 Bonus 4 - Networking & Building in public
14:30 Bonus 5 - Repeat
15:17 Conclusion
π ChatGPT playlist youtube.com/watch?v=Nj_zUMVuRUg&list=PLtqF5YXg7GLk696DOK7hpj6AGkYdWAPSE
π Streamlit playlist youtube.com/watch?v=ZZ4B0QUHuNc&list=PLtqF5YXg7GLmCvTswG32NqQypOuYkPRUE
π Books mentioned in video
9:49 amzn.to/3BmjEhZ
9:54 amzn.to/41xrIHi
10:00 amzn.to/41u4SAg
10:05 amzn.to/3M5lV63
10:13 amzn.to/44WIItc
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π Connect with Jess Haberman on LinkedIn linkedin.com/in/jhaberman
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#datascience #machinelearning #dataprofessor
1. Hackathon deadline
ποΈ May 5, 2023
2. App-building criteria
1οΈβ£ Build Streamlit app that connects to Snowflake data OR
2οΈβ£ Build Streamlit app for work
3. Resources to get you started in using Streamlit with Snowflake
π How to connect Streamlit to Snowflake youtube.com/watch?v=SgWxkAdjK78
π Building a Data Application with Snowflake Marketplace, Snowpark, and Streamlit youtube.com/watch?v=or0eeWIcDrg
4. Ideas for the app
π How to Create an ML Visualization & Monitoring App With Streamlit on Snowflake phdata.io/blog/how-to-create-an-ml-visualization-and-monitoring-app-with-streamlit-on-snowflake
5. Tips
π Hackathon 101: 5 simple tips for beginners blog.streamlit.io/hackathon-101-5-simple-tips-for-beginners
So what are you waiting for? Ready, set, build!
π οΈ About the Hackathon discuss.streamlit.io/t/enter-the-summit-hackathon/40473
βοΈ Submit your hackathon entry forms.streamlit.io/summit-hackathon
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π Learn more about BrightData and follow along get.brightdata.com/dataprofessor
π Code for webscraping on BrightData github.com/dataprofessor/youtube-data-scripts
π Code for app github.com/dataprofessor/youtube-data-app
πΉ Demo app https://youtube-data-channels.streamlit.app/
β° Timeline:
0:00 Introduction
1:25 Designing the app
3:31 Preview of data app
6:11 BrightData for web scraping
8:49 Exploring the webscraped JSON data
9:36 Walkthrough of the code
12:30 Next steps
13:22 Conclusion
πΌοΈ Credit:
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Problem solving flaticon.com/free-icon/problem-solving_4133585
Data collection flaticon.com/free-icon/data-collection_9409659
Data flaticon.com/free-icon/data_1197409
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IP flaticon.com/free-icon/ip_1674968
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π Check out ChatGPT chat.openai.com
π Animated-GIF Streamlit app youtu.be/OQv1jnw9_5s
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πΉοΈ Try ChatGPT chat.openai.com
π Example research article peerj.com/articles/11716
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