Learn the foundations of TensorFlow in Python, starting with tensors and working up to building and training neural networks with Keras. We cover what tensors are, how shapes and data types work, how TensorFlow handles device placement on CPUs and GPUs, and how Keras helps you build models using the Sequential API, Functional API, and model subclassing. Then we walk through the basic training workflow: compiling a model, choosing an optimizer and loss function, training with batches and epochs, validating results, and using callbacks like early stopping and model checkpoints. This is a practical introduction for Python programmers who want to understand how TensorFlow works without skipping the core ideas. Python Merch from Socratica: https://shop.socratica.com/collections/python-merch Support Socratica on Patreon: https://www.patreon.com/socratica

Tensors are the primary data structure in PyTorch. They are used to store data, perform mathematical operations, move computations between the CPU and GPU, and build the foundation for neural networks. In this lesson, we introduce PyTorch tensors from the ground up. We create 1D and 2D tensors, inspect tensor shape, data type, and device, then work through common tensor operations including addition, scalar multiplication, element-wise multiplication, matrix multiplication, broadcasting, reshaping, reduction operations, and indexing. We also look at GPU support in PyTorch and show how tensors can be moved to CUDA when a compatible GPU is available. Topics covered: * What tensors are * Creating tensors with `torch.tensor()` * Tensor shape, dtype, and device * Tensor addition and in-place operations * Scalar, element-wise, and matrix multiplication * Broadcasting * Reshaping tensors * Sum, mean, and max operations * Boolean masking and indexing * Moving tensors between CPU and GPU This is a practical introduction for Python programmers who want to understand the basic data structure behind PyTorch and deep learning. Support Socratica on Patreon: https://www.patreon.com/socratica

Probability Density Functions (PDFs) are essential for working with continuous random variables—but they can feel unintuitive at first. This lesson walks through the transition from discrete probability (probability mass functions) to continuous probability, where outcomes are infinite and probabilities behave differently. You will learn what a PDF is, how it works, and how to interpret probabilities over intervals. Topics covered: - Discrete vs. continuous random variables - Why probabilities “break” in the continuous case - What a Probability Density Function (PDF) really represents - Why probabilities at single points are zero - How to compute probabilities using areas under a curve This video is designed for students studying probability, statistics, or data science who want a clear, rigorous understanding of PDFs. We'd like to send a special thank you to our VIP Patrons at Patreon! Our patrons are the ones who make it possible for us to take the time to research, write, record, and edit these videos. Their support also makes it possible for us to invest in computers and software powerful enough to do the editing! Tracy Karin Prell Umar Khan Thomas Myers Michael Shebanow Marcos Silveira M Andrews KW Kevin B John Krawiec John-Michael Lewis Jeremy Shimanek Eric Eccleston and Christopher Kemsley are our VIP Patrons! 𝙅𝙊𝙄𝙉 this channel to get access to small Youtube perks like an owl emoji when you leave comments, fancy! https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Thank you, kind friends! 💜🦉 𝘽𝙚𝙘𝙤𝙢𝙚 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙤𝙣 𝙤𝙣 𝙋𝙖𝙩𝙧𝙚𝙤𝙣: https://www.patreon.com/socratica 📚 𝙒𝙚 𝙧𝙚𝙘𝙤𝙢𝙢𝙚𝙣𝙙 (affiliate links): The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow https://amzn.to/4j9n0YP The Art of Statistics: How to Learn from Data by David Spiegelhalter https://amzn.to/3S9E46a How to Be a Great Student (from Socratica!) ebook: https://amzn.to/2Lh3XSP paperback: https://amzn.to/3t5jeH3 🎬 𝘾𝙍𝙀𝘿𝙄𝙏𝙎: Written & Produced by: Michael Harrison & Kimberly Hatch Harrison Edited by: Alivia Brown Music License from Soundstripe Code: PZNWNZ5CCHZS09Q8 🎓 𝘼𝘽𝙊𝙐𝙏 𝙊𝙐𝙍 𝙄𝙉𝙎𝙏𝙍𝙐𝘾𝙏𝙊𝙍𝙎: Michael earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. Kimberly earned her BS in Biology and another BS in English at Caltech. She did her graduate work in Molecular Biology at Princeton, specializing in Immunology and Neurobiology. Kimberly spent 16+ years as a research scientist and a dozen years as a biology and chemistry instructor. Michael and Kimberly Harrison co-founded Socratica. Their mission? To create the education of the future. Ready to 🧠 𝙇𝙀𝘼𝙍𝙉 𝙈𝙊𝙍𝙀 with Socratica? 📺 𝙎𝙪𝙗𝙨𝙘𝙧𝙞𝙗𝙚 for SMART videos in Math, Science & Programming: http://bit.ly/SocraticaSubscribe ▶️ 𝙋𝙇𝘼𝙔𝙇𝙄𝙎𝙏𝙎: Study Tips http://bit.ly/StudyTipsPlaylist Python http://bit.ly/PythonSocratica Chemistry http://bit.ly/Chemistry_Playlist Calculus http://bit.ly/CalculusSocratica Geometry http://bit.ly/GeometrySocratica #probability #ProbabilityDensityFunctions #ContinuousRandomVariables

𝙎𝙄𝙂𝙉 𝙐𝙋 for tastefully infrequent updates about our upcoming Probability & Statistics course. 💌 https://snu.socratica.com/probability-statistics-course How do you calculate probabilities for a random variable with infinitely many outcomes? Your instinct may be to reuse what you learned when modeling coin flips and dice rolls. But transitioning from the finite to the infinite requires a shift in thinking. The math of discrete random variables and continuous random variables are fundamentally different. Today, let's explore the infinite world of continuous random variables. We'd like to send a special thank you to our VIP Patrons at Patreon! Our patrons are the ones who make it possible for us to take the time to research, write, record, and edit these videos. Their support also makes it possible for us to invest in computers and software powerful enough to do the editing! Tracy Karin Prell Umar Khan Thomas Myers Michael Shebanow Marcos Silveira M Andrews KW Kevin B John Krawiec John-Michael Lewis Jeremy Shimanek Eric Eccleston and Christopher Kemsley are our VIP Patrons! 𝙅𝙊𝙄𝙉 this channel to get access to small Youtube perks like an owl emoji when you leave comments, fancy! https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Thank you, kind friends! 💜🦉 𝘽𝙚𝙘𝙤𝙢𝙚 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙤𝙣 𝙤𝙣 𝙋𝙖𝙩𝙧𝙚𝙤𝙣: https://www.patreon.com/socratica 📚 𝙒𝙚 𝙧𝙚𝙘𝙤𝙢𝙢𝙚𝙣𝙙 (affiliate links): The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow https://amzn.to/4j9n0YP The Art of Statistics: How to Learn from Data by David Spiegelhalter https://amzn.to/3S9E46a How to Be a Great Student (from Socratica!) ebook: https://amzn.to/2Lh3XSP paperback: https://amzn.to/3t5jeH3 🎬 𝘾𝙍𝙀𝘿𝙄𝙏𝙎: Written & Produced by: Michael Harrison & Kimberly Hatch Harrison Edited by: Alivia Brown Music License from Soundstripe Code: VRTYMRUDPDTE6VTT 🎓 𝘼𝘽𝙊𝙐𝙏 𝙊𝙐𝙍 𝙄𝙉𝙎𝙏𝙍𝙐𝘾𝙏𝙊𝙍𝙎: Michael earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. Kimberly earned her BS in Biology and another BS in English at Caltech. She did her graduate work in Molecular Biology at Princeton, specializing in Immunology and Neurobiology. Kimberly spent 16+ years as a research scientist and a dozen years as a biology and chemistry instructor. Michael and Kimberly Harrison co-founded Socratica. Their mission? To create the education of the future. Ready to 🧠 𝙇𝙀𝘼𝙍𝙉 𝙈𝙊𝙍𝙀 with Socratica? 📺 𝙎𝙪𝙗𝙨𝙘𝙧𝙞𝙗𝙚 for SMART videos in Math, Science & Programming: http://bit.ly/SocraticaSubscribe ▶️ 𝙋𝙇𝘼𝙔𝙇𝙄𝙎𝙏𝙎: Study Tips http://bit.ly/StudyTipsPlaylist Python http://bit.ly/PythonSocratica Chemistry http://bit.ly/Chemistry_Playlist Calculus http://bit.ly/CalculusSocratica Geometry http://bit.ly/GeometrySocratica #probability #discretedistributions #randomvariables

Our intro to Matplotlib in Python, focusing on how to turn raw data into beautiful plots. We start by creating basic plots, then builds toward customizing figures, working with multiple datasets, and adjusting elements like labels, styles, and layouts. We introduce line plots,. histograms, pie charts, and more. Support Socratica on Patreon: https://www.patreon.com/socratica Join this channel to get access to perks: https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join

𝙎𝙄𝙂𝙉 𝙐𝙋 for tastefully infrequent updates about our upcoming Probability & Statistics course. 💌 https://snu.socratica.com/probability-statistics-course Probability has a basic language used to describe the world of randomness. We use words like "probably", "chance", and "what are the odds" in everyday language. But to successfully learn probability you need to be comfortable with precise terms like "random variables", "discrete distributions", and "PDFs." Coincidentally, our friend and fellow #EduTuber @AlexDainisPhD has been researching what people mean when they use that qualitative language "likely," "probably," etc. How LIKELY is likely? ▶️ https://youtube.com/shorts/mGeFy-kzyjo?si=_2rQZm9o9-P8x_Zf We'd like to send a special thank you to our VIP Patrons at Patreon! Our patrons are the ones who make it possible for us to take the time to research, write, record, and edit these videos. Their support also makes it possible for us to invest in computers and software powerful enough to do the editing! Tracy Karin Prell Umar Khan Thomas Myers Michael Shebanow Marcos Silveira M Andrews KW Kevin B John Krawiec John-Michael Lewis Jeremy Shimanek Eric Eccleston and Christopher Kemsley are our VIP Patrons! 𝙅𝙊𝙄𝙉 this channel to get access to small Youtube perks like an owl emoji when you leave comments, fancy! https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Thank you, kind friends! 💜🦉 𝘽𝙚𝙘𝙤𝙢𝙚 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙤𝙣 𝙤𝙣 𝙋𝙖𝙩𝙧𝙚𝙤𝙣: https://www.patreon.com/socratica 📚 𝙒𝙚 𝙧𝙚𝙘𝙤𝙢𝙢𝙚𝙣𝙙 (affiliate links): The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow https://amzn.to/4j9n0YP The Art of Statistics: How to Learn from Data by David Spiegelhalter https://amzn.to/3S9E46a How to Be a Great Student (from Socratica!) ebook: https://amzn.to/2Lh3XSP paperback: https://amzn.to/3t5jeH3 🎬 𝘾𝙍𝙀𝘿𝙄𝙏𝙎: Written & Produced by: Michael Harrison & Kimberly Hatch Harrison Edited by: Alivia Brown and Megi Shuke Music License from Soundstripe Code: EXOATJY9IIPBV422 🎓 𝘼𝘽𝙊𝙐𝙏 𝙊𝙐𝙍 𝙄𝙉𝙎𝙏𝙍𝙐𝘾𝙏𝙊𝙍𝙎: Michael earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. Kimberly earned her BS in Biology and another BS in English at Caltech. She did her graduate work in Molecular Biology at Princeton, specializing in Immunology and Neurobiology. Kimberly spent 16+ years as a research scientist and a dozen years as a biology and chemistry instructor. Michael and Kimberly Harrison co-founded Socratica. Their mission? To create the education of the future. Ready to 🧠 𝙇𝙀𝘼𝙍𝙉 𝙈𝙊𝙍𝙀 with Socratica? 📺 𝙎𝙪𝙗𝙨𝙘𝙧𝙞𝙗𝙚 for SMART videos in Math, Science & Programming: http://bit.ly/SocraticaSubscribe ▶️ 𝙋𝙇𝘼𝙔𝙇𝙄𝙎𝙏𝙎: Study Tips http://bit.ly/StudyTipsPlaylist Python http://bit.ly/PythonSocratica Chemistry http://bit.ly/Chemistry_Playlist Calculus http://bit.ly/CalculusSocratica Geometry http://bit.ly/GeometrySocratica #probability #discretedistributions #randomvariables

SciPy is a collection of specialized modules built on top of NumPy for more advanced scientific computations. We show how SciPy handles constants, numerical integration, optimization, linear algebra, and statistical analysis, with practical examples like retrieving physical constants, performing unit conversions, solving equations, and working with eigenvalues. Join this channel to get access to perks: https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Subscribe to Socratica: http://bit.ly/SocraticaSubscribe Support Socratica on Patreon: https://www.patreon.com/socratica Music License Code: UQCYAYM62SSKJQBR

𝙎𝙄𝙂𝙉 𝙐𝙋 for tastefully infrequent updates about our upcoming Probability & Statistics course. 💌 https://snu.socratica.com/probability-statistics-course Coins, dice, and even random integers all have something in common: a set of distinct outcomes you can list. That’s the world of discrete random variables. Here we compare & contrast discrete and continuous random variables and learn the rules a discrete distribution must follow. We'll even see a surprising case where there are infinitely many outcomes but the distribution is still discrete! ▶️ 𝙒𝘼𝙏𝘾𝙃 𝙉𝙀𝙓𝙏: Normal Distributions https://youtu.be/xlxaa9YhT6A We'd like to send a special thank you to our VIP Patrons at Patreon! Our patrons are the ones who make it possible for us to take the time to research, write, record, and edit these videos. Their support also makes it possible for us to invest in computers and software powerful enough to do the editing! Tracy Karin Prell Umar Khan Thomas Myers Michael Shebanow Marcos Silveira M Andrews KW Kevin B John Krawiec John-Michael Lewis Jeremy Shimanek Eric Eccleston and Christopher Kemsley are our VIP Patrons! 𝙅𝙊𝙄𝙉 this channel to get access to small Youtube perks like an owl emoji when you leave comments, fancy! https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Thank you, kind friends! 💜🦉 𝘽𝙚𝙘𝙤𝙢𝙚 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙤𝙣 𝙤𝙣 𝙋𝙖𝙩𝙧𝙚𝙤𝙣: https://www.patreon.com/socratica 📚 𝙒𝙚 𝙧𝙚𝙘𝙤𝙢𝙢𝙚𝙣𝙙 (affiliate links): The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow https://amzn.to/4j9n0YP The Art of Statistics: How to Learn from Data by David Spiegelhalter https://amzn.to/3S9E46a How to Be a Great Student (from Socratica!) ebook: https://amzn.to/2Lh3XSP paperback: https://amzn.to/3t5jeH3 🎬 𝘾𝙍𝙀𝘿𝙄𝙏𝙎: Written & Produced by: Michael Harrison & Kimberly Hatch Harrison Edited by: Alivia Brown and Megi Shuke Music License from Soundstripe Code: MSWKCNZ1WFQTCX2S 🎓 𝘼𝘽𝙊𝙐𝙏 𝙊𝙐𝙍 𝙄𝙉𝙎𝙏𝙍𝙐𝘾𝙏𝙊𝙍𝙎: Michael earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. Kimberly earned her BS in Biology and another BS in English at Caltech. She did her graduate work in Molecular Biology at Princeton, specializing in Immunology and Neurobiology. Kimberly spent 16+ years as a research scientist and a dozen years as a biology and chemistry instructor. Michael and Kimberly Harrison co-founded Socratica. Their mission? To create the education of the future. Ready to 🧠 𝙇𝙀𝘼𝙍𝙉 𝙈𝙊𝙍𝙀 with Socratica? 📺 𝙎𝙪𝙗𝙨𝙘𝙧𝙞𝙗𝙚 for SMART videos in Math, Science & Programming: http://bit.ly/SocraticaSubscribe ▶️ 𝙋𝙇𝘼𝙔𝙇𝙄𝙎𝙏𝙎: Study Tips http://bit.ly/StudyTipsPlaylist Python http://bit.ly/PythonSocratica Chemistry http://bit.ly/Chemistry_Playlist Calculus http://bit.ly/CalculusSocratica Geometry http://bit.ly/GeometrySocratica #probability #DiscreteDistributions #randomvariables

𝙅𝙤𝙞𝙣 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙚𝙤𝙣: https://www.patreon.com/cw/socratica 𝙎𝙞𝙜𝙣 𝙪𝙥 𝙛𝙤𝙧 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙤𝙪𝙧𝙨𝙚𝙨: https://www.socratica.com/collections 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝙋𝙮𝙩𝙝𝙤𝙣 𝙨𝙝𝙞𝙧𝙩: https://shop.socratica.com/products/python-by-socratica NumPy arrays are the foundation of numerical computing in Python. In this lesson, we walk through what they are, how they differ from regular Python lists, and why they are dramatically faster for mathematical work. We create arrays from lists, examine their shape, size, data type, and dimensions, and work through indexing, slicing, and reshaping multi-dimensional data. We also demonstrate vectorized operations, broadcasting, and element-wise arithmetic so you can see how NumPy replaces slow Python loops with efficient array-wide computation. All examples are written in plain Python and run step by step, giving you a practical understanding of how NumPy handles real numerical workloads in data science and machine learning. 📌 Patreon support keeps these videos coming: patreon.com/socratica 📺 More Python, math, and computer science at Socratica.com 𝙎𝙞𝙜𝙣 𝙪𝙥 𝙛𝙤𝙧 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙤𝙪𝙧𝙨𝙚𝙨: https://www.socratica.com/collections 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝙋𝙮𝙩𝙝𝙤𝙣 𝙨𝙝𝙞𝙧𝙩: https://shop.socratica.com/products/python-by-socratica 𝙋𝙧𝙤𝙜𝙧𝙖𝙢𝙢𝙞𝙣𝙜 𝙥𝙡𝙖𝙮𝙡𝙞𝙨𝙩𝙨: Python: http://bit.ly/PythonSocratica SQL: http://bit.ly/SQL_Socratica Subscribe to Socratica + bell for notifications: http://bit.ly/SocraticaSubscribe ⧓⧓⧓⧓⧓ We recommend: How to Be a Great Student ebook: https://amzn.to/2Lh3XSP Paperback: https://amzn.to/3t5jeH3 Kindle Unlimited (read free): https://amzn.to/3atr8TJ Python Cookbook, 3rd edition https://amzn.to/3jprjX2 More Socratica Python goodies here: https://shop.socratica.com/collections/python-merch ⧓⧓⧓⧓⧓ Join this channel to get access to perks: https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Support Socratica on Patreon: https://www.patreon.com/socratica Python instructor: Ulka Simone Mohanty (@ulkam on Twitter) Written & Produced by Michael Harrison Edited by Megi Shuke and Michael Harrison MUSIC CODE: QKQPL72XZ2MWZWNB #python #numpy #arrays

𝙎𝙏𝙊𝘾𝙆 𝙊𝙋𝙏𝙄𝙊𝙉𝙎 𝘾𝙊𝙐𝙍𝙎𝙀: https://www.socratica.com/courses/stock-options Stock options can amplify gains, but they also amplify risk. In this video, we break down the core risks every options trader must understand: directional risk, leverage, time decay, volatility and IV crush, liquidity and bid–ask spreads, interest rate changes, event risk, and assignment. 𝙌𝙐𝘼𝙉𝙏𝙄𝙏𝘼𝙏𝙄𝙑𝙀 𝙁𝙄𝙉𝘼𝙉𝘾𝙀 is where math meets the market. It is a supremely rational, logical approach to finance. It involves analyzing large datasets, generating mathematical models to make predictions about how markets will behave. Then, in application of these models, traders buy and sell securities based on those predictions. In this course, you will learn the key tools used by "quants." Our first course in Quantitative Finance focuses on stock options. Sign up here: 𝙎𝙏𝙊𝘾𝙆 𝙊𝙋𝙏𝙄𝙊𝙉𝙎 𝘾𝙊𝙐𝙍𝙎𝙀: https://www.socratica.com/courses/stock-options 𝙒𝙀 𝙍𝙀𝘾𝙊𝙈𝙈𝙀𝙉𝘿 Paul Wilmott Introduces Quantitative Finance 📘 https://amzn.to/3Qe8zab The Big Short (movie) 🎬 https://amzn.to/4jbl5DJ 𝘼𝘽𝙊𝙐𝙏 our Instructor: Michael Harrison earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. 𝙎𝙐𝘽𝙎𝘾𝙍𝙄𝘽𝙀 to Socratica: 🦉 http://bit.ly/SocraticaSubscribe 𝙎𝙐𝙋𝙋𝙊𝙍𝙏 Socratica on Patreon: 🅿️ https://www.patreon.com/socratica We'd like to send a special thank you to our VIP Patrons at Patreon! Our patrons are the ones who make it possible for us to take the time to research, write, record, and edit these videos. Their support also makes it possible for us to invest in computers and software powerful enough to do the editing! Tracy Karin Prell Umar Khan Thomas Myers Michael Shebanow Marcos Silveira M Andrews KW Kevin B John Krawiec John-Michael Lewis Jeremy Shimanek Eric Eccleston and Christopher Kemsley are our VIP Patrons! 𝙅𝙊𝙄𝙉 this channel to get access to small Youtube perks like an owl emoji when you leave comments, fancy! https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Music licensed from SoundStripe #Quants #StockOptions #Risk

𝙅𝙤𝙞𝙣 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙚𝙤𝙣: https://www.patreon.com/cw/socratica 𝙎𝙞𝙜𝙣 𝙪𝙥 𝙛𝙤𝙧 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙤𝙪𝙧𝙨𝙚𝙨: https://www.socratica.com/collections 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝙋𝙮𝙩𝙝𝙤𝙣 𝙨𝙝𝙞𝙧𝙩: https://shop.socratica.com/products/python-by-socratica Turn Python scripts into real desktop apps. We present an introduction to tkinter, Python’s built-in GUI toolkit. We start with the smallest possible window, then steadily add widgets, layouts, events, variables, and real interaction. For the grand finale we'll construct a fully unhinged Mars landing permit application. What you will see: - Creating your first Tkinter window - Labels, buttons, entries, and text fields - pack, grid, and why layout actually matters - Event handling with buttons and keyboard input - StringVar, IntVar, and proper widget state management - Combo boxes, radio buttons, checkboxes, and text areas - Clean, readable GUI code that does not fight you This is real Python, real widgets, and real patterns you can reuse. If your terminal feels a little too… monochrome, this is your way out. 📌 Patreon support keeps these videos coming: patreon.com/socratica 📺 More Python, math, and computer science at Socratica.com 𝙎𝙞𝙜𝙣 𝙪𝙥 𝙛𝙤𝙧 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙤𝙪𝙧𝙨𝙚𝙨: https://www.socratica.com/collections 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝙋𝙮𝙩𝙝𝙤𝙣 𝙨𝙝𝙞𝙧𝙩: https://shop.socratica.com/products/python-by-socratica 𝙋𝙧𝙤𝙜𝙧𝙖𝙢𝙢𝙞𝙣𝙜 𝙥𝙡𝙖𝙮𝙡𝙞𝙨𝙩𝙨: Python: http://bit.ly/PythonSocratica SQL: http://bit.ly/SQL_Socratica Subscribe to Socratica + bell for notifications: http://bit.ly/SocraticaSubscribe ⧓⧓⧓⧓⧓ We recommend: How to Be a Great Student ebook: https://amzn.to/2Lh3XSP Paperback: https://amzn.to/3t5jeH3 Kindle Unlimited (read free): https://amzn.to/3atr8TJ Python Cookbook, 3rd edition https://amzn.to/3jprjX2 More Socratica Python goodies here: https://shop.socratica.com/collections/python-merch ⧓⧓⧓⧓⧓ Join this channel to get access to perks: https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Support Socratica on Patreon: https://www.patreon.com/socratica Python instructor: Ulka Simone Mohanty (@ulkam on Twitter) Written & Produced by Michael Harrison Edited by Megi Shuke and Michael Harrison #python #tkinter #widget

𝙎𝙞𝙜𝙣 𝙪𝙥 𝙛𝙤𝙧 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙤𝙪𝙧𝙨𝙚𝙨: https://www.socratica.com/collections 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝙋𝙮𝙩𝙝𝙤𝙣 𝙨𝙝𝙞𝙧𝙩: https://shop.socratica.com/products/python-by-socratica HTTP is how clients and servers communicate on the web. In this lesson, we use Python’s requests library to send HTTP requests, inspect responses, work with JSON, handle errors, and manage sessions. Make sure you are subscribed to Socratica and you turn on notifications, so you don't miss the next lesson, which will focus on the server side. 𝙋𝙧𝙤𝙜𝙧𝙖𝙢𝙢𝙞𝙣𝙜 𝙥𝙡𝙖𝙮𝙡𝙞𝙨𝙩𝙨: Python: http://bit.ly/PythonSocratica SQL: http://bit.ly/SQL_Socratica Subscribe to Socratica + bell for notifications: http://bit.ly/SocraticaSubscribe ⧓⧓⧓⧓⧓ We recommend: How to Be a Great Student ebook: https://amzn.to/2Lh3XSP Paperback: https://amzn.to/3t5jeH3 Kindle Unlimited (read free): https://amzn.to/3atr8TJ Python Cookbook, 3rd edition https://amzn.to/3jprjX2 More Socratica Python goodies here: https://shop.socratica.com/collections/python-merch ⧓⧓⧓⧓⧓ Join this channel to get access to perks: https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Support Socratica on Patreon: https://www.patreon.com/socratica Python instructor: Ulka Simone Mohanty (@ulkam on Twitter) Written & Produced by Michael Harrison Edited by Megi Shuke and Michael Harrison #python #HTTPClient #httprequests

𝙎𝙞𝙜𝙣 𝙪𝙥 𝙛𝙤𝙧 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙤𝙪𝙧𝙨𝙚𝙨: https://www.socratica.com/collections 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝙋𝙮𝙩𝙝𝙤𝙣 𝙨𝙝𝙞𝙧𝙩: https://shop.socratica.com/products/python-by-socratica Threading allows Python programs to run multiple tasks concurrently within a single process. In this video, we introduce the threading module, show how to create and manage threads, and explain when threading improves performance. We also cover thread synchronization with locks and queues, and discuss important limitations like the Global Interpreter Lock (GIL). 𝙋𝙧𝙤𝙜𝙧𝙖𝙢𝙢𝙞𝙣𝙜 𝙥𝙡𝙖𝙮𝙡𝙞𝙨𝙩𝙨: Python: http://bit.ly/PythonSocratica SQL: http://bit.ly/SQL_Socratica Subscribe to Socratica + bell for notifications: http://bit.ly/SocraticaSubscribe ⧓⧓⧓⧓⧓ We recommend: How to Be a Great Student ebook: https://amzn.to/2Lh3XSP Paperback: https://amzn.to/3t5jeH3 Kindle Unlimited (read free): https://amzn.to/3atr8TJ Python Cookbook, 3rd edition https://amzn.to/3jprjX2 More Socratica Python goodies here: https://shop.socratica.com/collections/python-merch ⧓⧓⧓⧓⧓ Join this channel to get access to perks: https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Support Socratica on Patreon: https://www.patreon.com/socratica Python instructor: Ulka Simone Mohanty (@ulkam on Twitter) Written & Produced by Michael Harrison Edited by Megi Shuke and Michael Harrison #python #pythonprograming #OOP

𝙎𝙏𝙊𝘾𝙆 𝙊𝙋𝙏𝙄𝙊𝙉𝙎 𝘾𝙊𝙐𝙍𝙎𝙀: Our first finance course is 𝙉𝙊𝙒 𝙇𝙄𝙑𝙀! Aspiring quants should use this link to enroll: https://www.socratica.com/courses/stock-options Learn the essentials of trading with Stock Options. Everything from basic call and put options to more complex multi-leg strategies like straddles, spreads, collars, and more. Manage risk by monitoring The Greeks and stock volatility. This course is for sale on our website. You will pay once, and all future updates will be free. 𝘼𝘽𝙊𝙐𝙏 our Instructor: Michael Harrison earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. #StockOptions #Finance #Quant

𝙎𝙏𝙊𝘾𝙆 𝙊𝙋𝙏𝙄𝙊𝙉𝙎 𝘾𝙊𝙐𝙍𝙎𝙀: Our first finance course, Stock Options, is 𝙉𝙊𝙒 𝙇𝙄𝙑𝙀! Aspiring quants should use this link to enroll: https://www.socratica.com/courses/stock-options 𝙁𝙄𝙉𝘼𝙉𝘾𝙀 𝘾𝙊𝙐𝙍𝙎𝙀𝙎 from Socratica https://www.socratica.com/pages/finance-courses 🅿️ 𝘾𝙤𝙣𝙣𝙚𝙘𝙩 𝙬𝙞𝙩𝙝 𝙪𝙨 𝙤𝙣 𝙋𝘼𝙏𝙍𝙀𝙊𝙉 https://www.patreon.com/socratica 🎬𝙉𝙀𝙒 𝘾𝙊𝙐𝙍𝙎𝙀 𝘾𝙊𝙈𝙄𝙉𝙂 𝙎𝙊𝙊𝙉 - Quantitative Finance 𝙉𝙊𝙏𝙄𝙁𝙔 𝙈𝙀 𝙬𝙝𝙚𝙣 𝙩𝙝𝙚 𝙘𝙤𝙪𝙧𝙨𝙚 𝙡𝙖𝙪𝙣𝙘𝙝𝙚𝙨: 💌 https://snu.socratica.com/quantitative-finance Delta is the Greek that traders use every single day. It tells you how sensitive an option’s price is to moves in the underlying stock. In this lesson, we break Delta down from first principles. You will learn: - What Delta actually measures (with and without calculus) - How Delta behaves for calls and puts across the moneyness spectrum - Why Delta ranges from 0 to 1 for calls and 0 to –1 for puts - How traders interpret Delta as both exposure and probability - How to use Delta to estimate price changes in real trades - Why deep-in-the-money options behave like stock, and far-out-of-the-money options don’t - How Delta fits into the larger system of Greeks — and why Gamma is the natural next step We also work through practical examples with real numbers so you can immediately apply what you learn. 𝙌𝙐𝘼𝙉𝙏𝙄𝙏𝘼𝙏𝙄𝙑𝙀 𝙁𝙄𝙉𝘼𝙉𝘾𝙀 is where math meets the market. It is a supremely rational, logical approach to finance. It involves analyzing large datasets, generating mathematical models to make predictions about how markets will behave. Then, in application of these models, traders buy and sell securities based on those predictions. In this course, you will learn the key tools used by "quants." 𝙎𝙄𝙂𝙉 𝙐𝙋 𝙉𝙊𝙒: https://snu.socratica.com/quantitative-finance 𝙒𝙀 𝙍𝙀𝘾𝙊𝙈𝙈𝙀𝙉𝘿 Paul Wilmott Introduces Quantitative Finance 📘 https://amzn.to/3Qe8zab The Big Short (movie) 🎬 https://amzn.to/4jbl5DJ 𝘼𝘽𝙊𝙐𝙏 our Instructor: Michael Harrison earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. 𝙎𝙐𝘽𝙎𝘾𝙍𝙄𝘽𝙀 to Socratica: 🦉 http://bit.ly/SocraticaSubscribe 𝙎𝙐𝙋𝙋𝙊𝙍𝙏 Socratica on Patreon: 🅿️ https://www.patreon.com/socratica We'd like to send a special thank you to our VIP Patrons at Patreon! Our patrons are the ones who make it possible for us to take the time to do all the behind-the-scenes work to bring you these videos. Tracy Karin Prell Umar Khan Thomas Myers Michael Shebanow Mark Rushing Marcos Silveira M Andrews KW Kevin B John Krawiec John-Michael Lewis Jim Woodworth Jeremy Shimanek Eric Eccleston and Christopher Kemsley are our VIP Patrons! 𝙅𝙊𝙄𝙉 this channel to get access to small Youtube perks like an owl emoji when you leave comments, fancy! https://www.youtube.com/channel/UCW6TXMZ5Pq6yL6_k5NZ2e0Q/join Music Licensed from SoundStripe Code: TUQONPU7MIO8SBW6 #quant #stockoptions #delta