title
I Built a Sports Betting Bot with ChatGPT

description
I gave ChatGPT $2000 to make sports bets with and in this video i'll explain how we built the sports betting bot and whether it lost it all or made a potential total of $9,049.44 after 24 hours. First, a disclaimer - Do NOT invest any money in any type of sports betting bot or algorithmic engine that you are not willing to lose. I gave this sports betting bot money because I was willing to lose money to make a great video for my AI Wizards out there. To be exact, it was $1915.73 after transaction & conversion fees, which it used to bet on NBA teams that it predicted to win. Each week i'm learning more on how to optimally prompt ChatGPT to help me build MVPs, and it's a skill i'd like us all to learn, which is why i made this video. The tools used in this tutorial are the The Odds API for live sports data, Python for Programming, the Twitter API for Sentiment Analysis, PyTorch for Deep Learning, and Vercel for live deployment. Let me know what you think in the comments and I hope you have a great day today. Enjoy! Sports Betting Bot Code: https://github.com/llSourcell/ChatGPT_Sports_Betting_Bot Please Subscribe! That's what keeps me going. Proof of Settled Bets: https://polygonscan.com/address/0xaf3a394ddc02a5a80c60d4b36d7798ff0992611e Want more AI/ML education? Connect with me here: Twitter: https://twitter.com/sirajraval TikTok: https://www.tiktok.com/@sirajraval Facebook: https://www.facebook.com/sirajology Linkedin: https://www.linkedin.com/in/sirajraval/ Join the discord: https://discord.gg/zgEJxeYA2X I Built a Trading Bot with ChatGPT: https://www.youtube.com/watch?v=fhBw3j_O9LE Watch ChatGPT Build an AI Startup: https://www.youtube.com/watch?v=hL2hLFUwuqQ Watch ChatGPT Build a Finance Startup: https://www.youtube.com/watch?v=on623d5EfPw Watch Me Build a Startup Playlist: https://www.youtube.com/watch?v=oeraUtRgsbI&list=PL2-dafEMk2A4n3aP_rzgqA8lVGknkSN2p&index=1 Learn Machine Learning in 3 Months: https://www.youtube.com/watch?v=dS2HYPY7T-4 Join my AI community: http://chatgptschool.io/ Sign up for my AI Sports betting Bot, WagerGPT! (500 spots available): https://www.wagergpt.co

detail
{'title': 'I Built a Sports Betting Bot with ChatGPT', 'heatmap': [], 'summary': 'Showcases the development of a sports betting bot with chatgpt, generating $10,000 from an initial $2,000 through algorithm enhancements and twitter sentiment analysis, covering sports betting arbitrage techniques to achieve a 1% to 10% return, and building a sports betting model using twitter sentiment analysis and deep learning, achieving a $7,000 profit from two bets.', 'chapters': [{'end': 129.628, 'segs': [{'end': 29.715, 'src': 'embed', 'start': 0.149, 'weight': 0, 'content': [{'end': 0.75, 'text': 'Hello, world.', 'start': 0.149, 'duration': 0.601}, {'end': 5.176, 'text': "It's Siraj, and I built a sports betting bot with ChatGPT.", 'start': 0.87, 'duration': 4.306}, {'end': 10.182, 'text': "And in this app called GPT Wager, you can see that I've made two bets.", 'start': 5.336, 'duration': 4.846}, {'end': 15.389, 'text': 'The first one is about $1, 000 worth on the Golden State Warriors.', 'start': 10.242, 'duration': 5.147}, {'end': 19.491, 'text': 'The second one is about $1, 000 on the Brooklyn Nets.', 'start': 16.01, 'duration': 3.481}, {'end': 22.052, 'text': 'And this is because of my bot.', 'start': 20.091, 'duration': 1.961}, {'end': 24.773, 'text': "It's because of the predictions that it output.", 'start': 22.332, 'duration': 2.441}, {'end': 29.715, 'text': "And in this video, I'm gonna show you how I built this bot, what the results are at the end.", 'start': 25.273, 'duration': 4.442}], 'summary': "Siraj built a sports betting bot with chatgpt, placing $1000 bets on the golden state warriors and brooklyn nets based on the bot's predictions.", 'duration': 29.566, 'max_score': 0.149, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ149.jpg'}, {'end': 73.416, 'src': 'embed', 'start': 43.8, 'weight': 1, 'content': [{'end': 51.423, 'text': 'And the most important part of this video and what I really want to stress to you is mathematics and how awesome mathematics is.', 'start': 43.8, 'duration': 7.623}, {'end': 53.424, 'text': 'Mathematics helps you make money.', 'start': 51.603, 'duration': 1.821}, {'end': 56.165, 'text': "And in this video, we're going to start with a very simple bot.", 'start': 53.804, 'duration': 2.361}, {'end': 57.446, 'text': "It's an arbitrage bot.", 'start': 56.225, 'duration': 1.221}, {'end': 58.246, 'text': "I'll explain what that is.", 'start': 57.466, 'duration': 0.78}, {'end': 61.668, 'text': "Then we'll improve it to be what's called an XGBoost bot.", 'start': 58.687, 'duration': 2.981}, {'end': 63.909, 'text': "We'll improve it again to be a deep learning bot.", 'start': 62.088, 'duration': 1.821}, {'end': 73.416, 'text': "Then we'll add deep learning plus sentiment analysis on Twitter so we can see what people are saying on Twitter about a team and use that to improve our sports betting model.", 'start': 64.25, 'duration': 9.166}], 'summary': 'Mathematics empowers money-making bots, evolving from arbitrage to xgboost to deep learning, integrating sentiment analysis for sports betting.', 'duration': 29.616, 'max_score': 43.8, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ43800.jpg'}, {'end': 107.608, 'src': 'embed', 'start': 83.122, 'weight': 3, 'content': [{'end': 88.643, 'text': 'That question is gonna be, show me a list of the top 10 most common math techniques.', 'start': 83.122, 'duration': 5.521}, {'end': 96.385, 'text': "Now remember, we love math, so we're gonna ask you about math techniques, and we're gonna be very direct to make money from sports betting.", 'start': 88.683, 'duration': 7.702}, {'end': 101.346, 'text': "You know, I've heard terms like arbitrage, and let's give it some context here.", 'start': 96.865, 'duration': 4.481}, {'end': 103.347, 'text': 'Remember, ChatGPT remembers context.', 'start': 101.386, 'duration': 1.961}, {'end': 107.608, 'text': "So I've heard terms like arbitrage and expected value betting.", 'start': 103.767, 'duration': 3.841}], 'summary': 'Top 10 common math techniques for sports betting include arbitrage and expected value betting.', 'duration': 24.486, 'max_score': 83.122, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ83122.jpg'}], 'start': 0.149, 'title': 'Creating a sports betting bot with chatgpt', 'summary': 'Showcases the development of a sports betting bot with chatgpt, generating $10,000 from an initial $2,000 through algorithm enhancements and twitter sentiment analysis, highlighting the significant impact of mathematics in sports betting profitability.', 'chapters': [{'end': 129.628, 'start': 0.149, 'title': 'Sports betting bot with chatgpt', 'summary': "Showcases the creation of a sports betting bot with chatgpt, making $10,000 from $2,000 through a series of improvements in the bot's algorithm and the addition of sentiment analysis from twitter, emphasizing the role of mathematics in making money from sports betting.", 'duration': 129.479, 'highlights': ['The bot made two bets, $1,000 each on the Golden State Warriors and the Brooklyn Nets.', 'The video demonstrates the progression from an arbitrage bot to XGBoost bot to a deep learning bot with added sentiment analysis on Twitter.', 'Emphasizes the significance of mathematics in enhancing the sports betting model and making money.', 'The chapter starts with a request to ChatGPT to show a list of the top 10 most common math techniques, focusing on utilizing math to profit from sports betting.', 'Discusses the use of arbitrage and expected value betting, highlighting the importance of understanding these concepts in sports betting.']}], 'duration': 129.479, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ149.jpg', 'highlights': ['The bot made two bets, $1,000 each on the Golden State Warriors and the Brooklyn Nets.', 'The video demonstrates the progression from an arbitrage bot to XGBoost bot to a deep learning bot with added sentiment analysis on Twitter.', 'Emphasizes the significance of mathematics in enhancing the sports betting model and making money.', 'Discusses the use of arbitrage and expected value betting, highlighting the importance of understanding these concepts in sports betting.', 'The chapter starts with a request to ChatGPT to show a list of the top 10 most common math techniques, focusing on utilizing math to profit from sports betting.']}, {'end': 557.581, 'segs': [{'end': 173.384, 'src': 'embed', 'start': 149.569, 'weight': 1, 'content': [{'end': 159.011, 'text': 'Then we have algebra, arithmetic, numbers, plus, minus, subtraction, division, and even calculus in the case of Markov chain Monte Carlo.', 'start': 149.569, 'duration': 9.442}, {'end': 166.497, 'text': "That's a way of simulating different outcomes and we can use calculus to find the rate of change or the derivative of different variables.", 'start': 159.031, 'duration': 7.466}, {'end': 173.384, 'text': 'So we can see 10 methods right off the bat that ChatGPT gave us to make money from sports betting.', 'start': 166.557, 'duration': 6.827}], 'summary': 'Chatgpt provides 10 methods for making money from sports betting.', 'duration': 23.815, 'max_score': 149.569, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ149569.jpg'}, {'end': 256.267, 'src': 'embed', 'start': 212.907, 'weight': 0, 'content': [{'end': 215.891, 'text': "What arbitrage betting is is it's saying that, hey,", 'start': 212.907, 'duration': 2.984}, {'end': 224.26, 'text': 'if I bet on all possible outcomes across a variety of sportsbooks because they all have different odds for the same outcomes,', 'start': 215.891, 'duration': 8.369}, {'end': 229.046, 'text': "I can find these inefficiencies in this market because it's very similar to a financial, like a stock market.", 'start': 224.26, 'duration': 4.786}, {'end': 230.448, 'text': "It's like a sports betting market.", 'start': 229.066, 'duration': 1.382}, {'end': 234.831, 'text': 'I can find very similar inefficiencies and then I can exploit them to make money.', 'start': 231.008, 'duration': 3.823}, {'end': 244.459, 'text': 'And so if the sum of the inverse of all of the probabilities of the odds of a given game are less than one,', 'start': 235.252, 'duration': 9.207}, {'end': 247.382, 'text': 'we can say that an arbitrage opportunity exists.', 'start': 244.459, 'duration': 2.923}, {'end': 256.267, 'text': 'So even if we make two bets in two different directions, if there is a real arbitrage opportunity, we can be guaranteed a return.', 'start': 247.822, 'duration': 8.445}], 'summary': 'Arbitrage betting exploits market inefficiencies in sportsbooks to guarantee a return on bets.', 'duration': 43.36, 'max_score': 212.907, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ212907.jpg'}, {'end': 369.614, 'src': 'embed', 'start': 339.94, 'weight': 3, 'content': [{'end': 340.4, 'text': 'Thank you.', 'start': 339.94, 'duration': 0.46}, {'end': 344.002, 'text': 'Show me a Python arbitrage bot for sports betting.', 'start': 341.82, 'duration': 2.182}, {'end': 346.243, 'text': 'Simple example that fits into one class file.', 'start': 344.102, 'duration': 2.141}, {'end': 348.444, 'text': "I think adding the math thing, it didn't like that.", 'start': 346.263, 'duration': 2.181}, {'end': 356.067, 'text': "So given that, using a single library and let's say three different bookmarkers, we can do a three-way arbitrage as well.", 'start': 348.484, 'duration': 7.583}, {'end': 357.968, 'text': "It's going to find that arbitrage.", 'start': 356.628, 'duration': 1.34}, {'end': 363.131, 'text': "So let's take this code And let's go to a Google Colab notebook, colab.research.google.com.", 'start': 357.988, 'duration': 5.143}, {'end': 364.471, 'text': "We'll open that notebook.", 'start': 363.451, 'duration': 1.02}, {'end': 369.614, 'text': "It's just an easy way to run Python code, even if you're not like a super good coder or anything.", 'start': 364.551, 'duration': 5.063}], 'summary': 'Python arbitrage bot finds three-way arbitrage using a single library and three bookmarkers.', 'duration': 29.674, 'max_score': 339.94, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ339940.jpg'}, {'end': 463.557, 'src': 'embed', 'start': 381.022, 'weight': 5, 'content': [{'end': 383.363, 'text': "So we've gotta get some legit sports data.", 'start': 381.022, 'duration': 2.341}, {'end': 384.863, 'text': "So let's ask it for some of that.", 'start': 383.403, 'duration': 1.46}, {'end': 389.664, 'text': "So that's gonna be our next question, going back to our original prompt series here.", 'start': 384.963, 'duration': 4.701}, {'end': 392.505, 'text': "And we're gonna say, show me, let's go back here.", 'start': 389.684, 'duration': 2.821}, {'end': 400.007, 'text': 'Show me a list of the top 10 open source odds APIs for sports betting.', 'start': 392.985, 'duration': 7.022}, {'end': 402.368, 'text': "We don't just want, we want several.", 'start': 400.347, 'duration': 2.021}, {'end': 413.423, 'text': "And I have gone through some of these and it can be quite a pain to find a developer API given whatever area of the world you're living in.", 'start': 403.576, 'duration': 9.847}, {'end': 420.328, 'text': 'So in the end, the one that I found that would work is the odds API.', 'start': 413.884, 'duration': 6.444}, {'end': 422.95, 'text': 'And here it is odds API right here.', 'start': 420.989, 'duration': 1.961}, {'end': 425.552, 'text': "So that's the one we're gonna use the odds API.", 'start': 423.43, 'duration': 2.122}, {'end': 432.457, 'text': 'Use the odds API in Python to pull NBA data.', 'start': 426.292, 'duration': 6.165}, {'end': 436.334, 'text': 'pull NBA data.', 'start': 434.773, 'duration': 1.561}, {'end': 438.877, 'text': "And then it's going to give that to us.", 'start': 437.576, 'duration': 1.301}, {'end': 444.402, 'text': "And then what we're gonna do is we're gonna sign up for the Odds API because we need that.", 'start': 438.937, 'duration': 5.465}, {'end': 446.403, 'text': 'And here it is, Odds API.', 'start': 444.922, 'duration': 1.481}, {'end': 448.645, 'text': 'We can see we need to get an API key.', 'start': 446.864, 'duration': 1.781}, {'end': 451.288, 'text': "It's gonna start out free, perfect, enter our name and everything.", 'start': 448.725, 'duration': 2.563}, {'end': 452.809, 'text': "Assume we've signed up for that.", 'start': 451.648, 'duration': 1.161}, {'end': 460.196, 'text': "And once we've signed up for that, we're gonna go back to the main page and we're gonna get that API key.", 'start': 453.309, 'duration': 6.887}, {'end': 463.557, 'text': "Where is it? It's under Account.", 'start': 460.776, 'duration': 2.781}], 'summary': 'Using odds api in python to pull nba data and sign up for the odds api for sports betting.', 'duration': 82.535, 'max_score': 381.022, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ381022.jpg'}], 'start': 130.089, 'title': 'Sports betting and odds api', 'summary': 'Covers mathematical techniques for sports betting arbitrage, focusing on exploiting odds inefficiencies to achieve a 1% to 10% return, and discusses utilizing the odds api for obtaining sports data with python examples and integration with google sheets.', 'chapters': [{'end': 381.002, 'start': 130.089, 'title': 'Sports betting arbitrage techniques', 'summary': 'Discusses various mathematical techniques including probability, statistics, algebra, and calculus, and focuses on arbitrage betting in sports, particularly the concept of exploiting inefficiencies in the odds market to make a 1% to 10% return.', 'duration': 250.913, 'highlights': ['Arbitrage betting involves exploiting inefficiencies in the odds market across different sportsbooks to make a guaranteed return, typically between 1% to 10%.', 'The chapter mentions the use of mathematics, particularly probability, statistics, algebra, and calculus, to analyze sports betting data and build an arbitrage bot.', 'The concept of finding arbitrage opportunities in the sports betting market is likened to exploiting inefficiencies in a stock market, with the goal of making a profit.', 'The speaker seeks a simple example of a Python arbitrage bot for sports betting that fits into a single class file, using a specific library and potentially exploring three-way arbitrage using three different bookmarkers.', 'The speaker expresses a need for a provably profitable strategy in sports betting and emphasizes the importance of understanding the mathematical principles behind the arbitrage technique.']}, {'end': 557.581, 'start': 381.022, 'title': 'Utilizing odds api for sports data in python', 'summary': 'Discusses the process of obtaining and utilizing sports data through the odds api, including signing up for the api, integrating it with google sheets, and using python examples to work with the data.', 'duration': 176.559, 'highlights': ['Signing up for the Odds API and obtaining the API key, which starts out free, is crucial for the process. Signing up for the Odds API is necessary to obtain the API key, which initially is free.', 'Utilizing the Odds API in Python to pull NBA data and integrating it with Google Sheets allows for the retrieval and organization of sports betting information. Using the Odds API in Python to pull NBA data and integrating it with Google Sheets enables the retrieval and organization of sports betting information.', 'The process involves obtaining a list of the top 10 open source odds APIs for sports betting, with the Odds API being the selected option due to its compatibility. The process includes obtaining a list of the top 10 open source odds APIs for sports betting, with the Odds API being the selected option due to its compatibility.']}], 'duration': 427.492, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ130089.jpg', 'highlights': ['Arbitrage betting exploits odds inefficiencies for 1% to 10% return.', 'Mathematics, including probability, statistics, algebra, and calculus, is used to analyze sports betting data.', 'Finding arbitrage opportunities in sports betting is akin to exploiting stock market inefficiencies.', 'Python arbitrage bot example seeks to explore three-way arbitrage using specific library.', 'Understanding mathematical principles is crucial for a provably profitable sports betting strategy.', 'Signing up for Odds API and obtaining API key is crucial for obtaining sports data.', 'Using Odds API in Python to pull NBA data and integrating it with Google Sheets organizes sports betting information.', 'Selecting Odds API from top 10 open source odds APIs for sports betting due to compatibility.']}, {'end': 826.005, 'segs': [{'end': 630.786, 'src': 'embed', 'start': 599.159, 'weight': 0, 'content': [{'end': 600.119, 'text': 'Thank you, Ryan, for this.', 'start': 599.159, 'duration': 0.96}, {'end': 601.879, 'text': 'And it was made four months ago.', 'start': 600.539, 'duration': 1.34}, {'end': 602.74, 'text': 'Very cool.', 'start': 602.28, 'duration': 0.46}, {'end': 605.06, 'text': "It's using the odds API.", 'start': 602.8, 'duration': 2.26}, {'end': 605.981, 'text': 'Okay, perfect.', 'start': 605.2, 'duration': 0.781}, {'end': 607.921, 'text': "That's exactly what we need to do.", 'start': 606.581, 'duration': 1.34}, {'end': 609.622, 'text': 'What arbitrage? Okay.', 'start': 608.021, 'duration': 1.601}, {'end': 611.502, 'text': "We didn't even have to do any of this work.", 'start': 610.182, 'duration': 1.32}, {'end': 612.703, 'text': "This guy's already done it for us.", 'start': 611.642, 'duration': 1.061}, {'end': 620.224, 'text': "And that is the value of getting good at searching for code on GitHub, because there's so much value to be found there.", 'start': 613.023, 'duration': 7.201}, {'end': 621.524, 'text': "So let's run this thing.", 'start': 620.264, 'duration': 1.26}, {'end': 626.265, 'text': "This guy's got an IPython notebook for us, and it's going to create an Excel spreadsheet.", 'start': 621.564, 'duration': 4.701}, {'end': 630.786, 'text': "Um, just like we found before the odds API, it's going to get all that.", 'start': 626.785, 'duration': 4.001}], 'summary': 'Using odds api, automated arbitrage through github code saved time and effort.', 'duration': 31.627, 'max_score': 599.159, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ599159.jpg'}, {'end': 684.511, 'src': 'embed', 'start': 657.071, 'weight': 2, 'content': [{'end': 660.432, 'text': "Now we open the zip and we're going to upload it to Google Colab.", 'start': 657.071, 'duration': 3.361}, {'end': 662.192, 'text': "So we'll go to colab.research.google.", 'start': 660.452, 'duration': 1.74}, {'end': 668.157, 'text': "we'll go to upload and then we're going to choose that and upload it to Google Colab.", 'start': 662.752, 'duration': 5.405}, {'end': 674.162, 'text': "but I've already uploaded it and it's right here, so we can go through this and run this ourselves.", 'start': 668.157, 'duration': 6.005}, {'end': 677.244, 'text': 'so once we install this pip repository,', 'start': 674.162, 'duration': 3.082}, {'end': 684.511, 'text': 'then we can just go right ahead and start compiling this code and see what this Excel spreadsheet that it gives us is going to be.', 'start': 677.244, 'duration': 7.267}], 'summary': 'Uploading zip to google colab and running code to generate excel spreadsheet.', 'duration': 27.44, 'max_score': 657.071, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ657071.jpg'}, {'end': 810.875, 'src': 'embed', 'start': 784.969, 'weight': 3, 'content': [{'end': 795.187, 'text': "i'd like to create a sports betting bot that makes bets daily for me on the winning team for the NBA.", 'start': 784.969, 'duration': 10.218}, {'end': 798.508, 'text': "Let's be very clear about it and let's give it our wildest fantasy.", 'start': 795.447, 'duration': 3.061}, {'end': 804.851, 'text': "Let's say it uses computer vision my favorite subfield of machine learning to watch all previous games,", 'start': 798.868, 'duration': 5.983}, {'end': 807.572, 'text': "so we don't have to sit there and watch them ourselves.", 'start': 804.851, 'duration': 2.721}, {'end': 810.875, 'text': 'as well as Twitter sentiment,', 'start': 807.572, 'duration': 3.303}], 'summary': 'Create sports betting bot for daily nba bets using computer vision and twitter sentiment analysis.', 'duration': 25.906, 'max_score': 784.969, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ784969.jpg'}], 'start': 557.621, 'title': 'Github search and sports betting bot', 'summary': 'Discusses searching for statistical arbitrage code on github and the process of compiling an excel spreadsheet, identifying arbitrage opportunities, and creating a sports betting bot using machine learning with a focus on statistics and artificial intelligence.', 'chapters': [{'end': 677.244, 'start': 557.621, 'title': 'Github search for statistical arbitrage', 'summary': 'Discusses the process of searching for statistical arbitrage code on github, finding an existing solution that utilizes the odds api, and the value of efficient code search, which led to saving time and effort in developing new functions and processes.', 'duration': 119.623, 'highlights': ['Finding existing solution for statistical arbitrage on GitHub that utilizes the odds API by Ryan Krumensnacher, saving time and effort in development.', 'Discussion about the data cleaning and data processing required for the odds API to be compiled with an arbitrage bot from ChatGPT.', 'Importance of efficient code search on GitHub for valuable solutions, showcasing the significance of the code repository for development.', 'Process of uploading the downloaded IPython notebook from GitHub to Google Colab for running and execution of the obtained solution.']}, {'end': 826.005, 'start': 677.244, 'title': 'Sports betting bot and machine learning', 'summary': 'Discusses the process of compiling code for an excel spreadsheet, identifying arbitrage opportunities, and the plan to create a sports betting bot using machine learning with a focus on statistics and artificial intelligence.', 'duration': 148.761, 'highlights': ['The arbitrage opportunity in the Excel spreadsheet indicates a potential profit of five bucks between two different bookmakers, Bovada and another one.', 'The plan to create a machine learning model for sports betting involves leveraging statistics and artificial intelligence, with a focus on techniques like linear algebra, calculus, and utilizing digital brains in the form of static files for better decision-making.', 'The vision for the sports betting bot includes using computer vision to analyze previous games and Twitter sentiment analysis to make daily bets on the winning team for the NBA, aiming to automate the betting process and incorporate additional data like Twitter sentiment and past statistics.']}], 'duration': 268.384, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ557621.jpg', 'highlights': ['Finding existing solution for statistical arbitrage on GitHub that utilizes the odds API by Ryan Krumensnacher, saving time and effort in development.', 'Importance of efficient code search on GitHub for valuable solutions, showcasing the significance of the code repository for development.', 'Process of uploading the downloaded IPython notebook from GitHub to Google Colab for running and execution of the obtained solution.', 'The vision for the sports betting bot includes using computer vision to analyze previous games and Twitter sentiment analysis to make daily bets on the winning team for the NBA, aiming to automate the betting process and incorporate additional data like Twitter sentiment and past statistics.', 'The plan to create a machine learning model for sports betting involves leveraging statistics and artificial intelligence, with a focus on techniques like linear algebra, calculus, and utilizing digital brains in the form of static files for better decision-making.']}, {'end': 1330.634, 'segs': [{'end': 906.241, 'src': 'embed', 'start': 876.601, 'weight': 3, 'content': [{'end': 877.703, 'text': 'So we have to do this ourselves.', 'start': 876.601, 'duration': 1.102}, {'end': 878.364, 'text': 'Okay, fine.', 'start': 877.863, 'duration': 0.501}, {'end': 879.766, 'text': "Let's just do this ourselves.", 'start': 878.604, 'duration': 1.162}, {'end': 886.816, 'text': 'So show me simple Python code to scrape Twitter for sentiment analysis.', 'start': 879.786, 'duration': 7.03}, {'end': 891.566, 'text': 'on the NBA Warriors team, just like the Warriors team.', 'start': 888.243, 'duration': 3.323}, {'end': 899.294, 'text': 'Can you do this simple thing for me, ChatGPT? Forget deep learning at scale with transformers and reinforcement learning.', 'start': 891.787, 'duration': 7.507}, {'end': 904.939, 'text': "Just, okay, it may violate the content policy, but you're still gonna give it to me.", 'start': 899.594, 'duration': 5.345}, {'end': 906.241, 'text': 'Thank you very much, OpenAI.', 'start': 904.999, 'duration': 1.242}], 'summary': 'Request for simple python code to scrape twitter for sentiment analysis on the nba warriors team.', 'duration': 29.64, 'max_score': 876.601, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ876601.jpg'}, {'end': 968.122, 'src': 'embed', 'start': 922.032, 'weight': 4, 'content': [{'end': 925.315, 'text': "And what TextBlob does is it's not super advanced machine learning.", 'start': 922.032, 'duration': 3.283}, {'end': 927.356, 'text': "What it's using is a lexicon.", 'start': 925.635, 'duration': 1.721}, {'end': 933.34, 'text': "And what a lexicon is is it's a dictionary of values that are correlated with different words.", 'start': 927.376, 'duration': 5.964}, {'end': 936.462, 'text': "So let's paste that into a Google Colab.", 'start': 933.44, 'duration': 3.022}, {'end': 946.666, 'text': "And it's going to ask us for our consumer key, our consumer secret, our access token, and our access token secret, as well as what team we want.", 'start': 936.902, 'duration': 9.764}, {'end': 950.587, 'text': 'And so in order to do that, we have to go to the developer portal on Twitter.', 'start': 946.766, 'duration': 3.821}, {'end': 955.449, 'text': 'And at the developer portal, we have to create a new test app.', 'start': 951.488, 'duration': 3.961}, {'end': 961.531, 'text': "Once we create that test app under settings, it's going to give us all of the keys that we need.", 'start': 955.809, 'duration': 5.722}, {'end': 968.122, 'text': "for that under manage, under app settings, here are the keys and tokens, and then we'll reveal them and insert that into our code.", 'start': 962.011, 'duration': 6.111}], 'summary': 'Textblob uses lexicon for sentiment analysis. keys are obtained from twitter developer portal.', 'duration': 46.09, 'max_score': 922.032, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ922032.jpg'}, {'end': 1146.28, 'src': 'embed', 'start': 1114.536, 'weight': 0, 'content': [{'end': 1121.36, 'text': "It's using a neural network with TensorFlow to predict the winning team, and then it's also using an XGBoost algorithm to predict the winning team,", 'start': 1114.536, 'duration': 6.824}, {'end': 1122.641, 'text': 'and then you can compare both of them.', 'start': 1121.36, 'duration': 1.281}, {'end': 1126.984, 'text': 'So what we can do is we can combine several things.', 'start': 1123.101, 'duration': 3.883}, {'end': 1132.848, 'text': "We can combine Kyle's model here with our Twitter sentiment analysis model.", 'start': 1127.024, 'duration': 5.824}, {'end': 1140.294, 'text': "We can say if Kyle's model predicts a winning team and our Twitter sentiment model says that this is going to be a very positive sentiment winning team,", 'start': 1132.868, 'duration': 7.426}, {'end': 1142.956, 'text': 'then we can bet on that winning team right?', 'start': 1140.914, 'duration': 2.042}, {'end': 1146.28, 'text': "And what we're gonna do is this is gonna give us a lot of numbers.", 'start': 1143.477, 'duration': 2.803}], 'summary': 'Using neural network and xgboost to predict winning team, and combining with twitter sentiment analysis for betting strategy.', 'duration': 31.744, 'max_score': 1114.536, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ1114536.jpg'}, {'end': 1329.273, 'src': 'embed', 'start': 1299.425, 'weight': 2, 'content': [{'end': 1301.546, 'text': "Let's see if I made money or lost money.", 'start': 1299.425, 'duration': 2.121}, {'end': 1304.925, 'text': "All right, it's the day after.", 'start': 1303.584, 'duration': 1.341}, {'end': 1306.165, 'text': 'And drum roll, please.', 'start': 1305.025, 'duration': 1.14}, {'end': 1311.067, 'text': 'It looks like the bot made $7, 000 from two bets.', 'start': 1306.965, 'duration': 4.102}, {'end': 1313.628, 'text': 'One for the Warriors and one for the Nets.', 'start': 1311.607, 'duration': 2.021}, {'end': 1314.988, 'text': 'Thank you, AI.', 'start': 1314.228, 'duration': 0.76}, {'end': 1317.209, 'text': 'All right, thank you guys so much for watching.', 'start': 1315.188, 'duration': 2.021}, {'end': 1320.33, 'text': 'I wanna keep making videos like this every single week.', 'start': 1317.729, 'duration': 2.601}, {'end': 1322.731, 'text': 'So if you wanna keep watching, please subscribe.', 'start': 1320.39, 'duration': 2.341}, {'end': 1324.752, 'text': "That's what really motivates me to continually do this.", 'start': 1322.791, 'duration': 1.961}, {'end': 1326.773, 'text': 'And like the video as well, that helps promote it.', 'start': 1325.152, 'duration': 1.621}, {'end': 1329.273, 'text': "For now, I've gotta go find the optimal prompt.", 'start': 1327.093, 'duration': 2.18}], 'summary': 'Ai bot made $7,000 from two bets on warriors and nets.', 'duration': 29.848, 'max_score': 1299.425, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ1299425.jpg'}], 'start': 827.926, 'title': 'Building twitter sentiment analysis and sports betting model', 'summary': 'Covers a tutorial on creating a twitter sentiment analysis tool with python flask, tweepy, and textblob, and discusses building a sports betting model using twitter sentiment analysis and deep learning, achieving a $7,000 profit from two bets.', 'chapters': [{'end': 968.122, 'start': 827.926, 'title': 'Python flask: twitter sentiment analysis', 'summary': "Provides a detailed tutorial on building a twitter sentiment analysis tool using python flask, tweepy, and textblob, as well as guidance on obtaining api keys for twitter's developer portal.", 'duration': 140.196, 'highlights': ['The chapter discusses using Tweepy, a Python wrapper for the Twitter API, to scrape Twitter for sentiment analysis on the NBA Warriors team. Tweepy is used to access the Twitter API for scraping data, providing a practical example of sentiment analysis on the NBA Warriors team.', 'The TextBlob library, which utilizes a lexicon for sentiment analysis, is introduced for analyzing Twitter data. TextBlob is explained as a tool for sentiment analysis using a lexicon, highlighting its approach as an alternative to advanced machine learning.', "Guidance is given on obtaining consumer key, consumer secret, access token, and access token secret from the Twitter developer portal for API access. Step-by-step instructions are provided for acquiring the necessary API keys and tokens from Twitter's developer portal to access the Twitter API for data scraping."]}, {'end': 1330.634, 'start': 968.583, 'title': 'Sports betting with ai', 'summary': 'Discusses building a sports betting model using twitter sentiment analysis and deep learning, integrating existing models, and making profitable bets, resulting in a $7,000 profit from two bets.', 'duration': 362.051, 'highlights': ["Integrating existing models Combining Kyle's NBA machine learning model with Twitter sentiment analysis to predict winning teams and make profitable bets, resulting in a $7,000 profit from two bets.", "Using Twitter sentiment analysis and deep learning Discussing the use of Twitter sentiment analysis and deep learning to predict sports outcomes, enhancing the betting model's accuracy and profitability.", 'Profitable bets resulting in a $7,000 profit Revealing the successful outcome of the sports betting model, resulting in a $7,000 profit from two bets, showcasing the effectiveness of the integrated models.']}], 'duration': 502.708, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/IDthta5sUGQ/pics/IDthta5sUGQ827926.jpg', 'highlights': ["Integrating existing models Combining Kyle's NBA machine learning model with Twitter sentiment analysis to predict winning teams and make profitable bets, resulting in a $7,000 profit from two bets.", "Using Twitter sentiment analysis and deep learning Discussing the use of Twitter sentiment analysis and deep learning to predict sports outcomes, enhancing the betting model's accuracy and profitability.", 'Profitable bets resulting in a $7,000 profit Revealing the successful outcome of the sports betting model, resulting in a $7,000 profit from two bets, showcasing the effectiveness of the integrated models.', 'The chapter discusses using Tweepy, a Python wrapper for the Twitter API, to scrape Twitter for sentiment analysis on the NBA Warriors team. Tweepy is used to access the Twitter API for scraping data, providing a practical example of sentiment analysis on the NBA Warriors team.', 'The TextBlob library, which utilizes a lexicon for sentiment analysis, is introduced for analyzing Twitter data. TextBlob is explained as a tool for sentiment analysis using a lexicon, highlighting its approach as an alternative to advanced machine learning.', "Guidance is given on obtaining consumer key, consumer secret, access token, and access token secret from the Twitter developer portal for API access. Step-by-step instructions are provided for acquiring the necessary API keys and tokens from Twitter's developer portal to access the Twitter API for data scraping."]}], 'highlights': ["Integrating existing models Combining Kyle's NBA machine learning model with Twitter sentiment analysis to predict winning teams and make profitable bets, resulting in a $7,000 profit from two bets.", 'The vision for the sports betting bot includes using computer vision to analyze previous games and Twitter sentiment analysis to make daily bets on the winning team for the NBA, aiming to automate the betting process and incorporate additional data like Twitter sentiment and past statistics.', 'The bot made two bets, $1,000 each on the Golden State Warriors and the Brooklyn Nets.', "Using Twitter sentiment analysis and deep learning Discussing the use of Twitter sentiment analysis and deep learning to predict sports outcomes, enhancing the betting model's accuracy and profitability.", 'The video demonstrates the progression from an arbitrage bot to XGBoost bot to a deep learning bot with added sentiment analysis on Twitter.']}