Siraj Raval

I'm going to build a medical imaging classification app called SmartMedScan! The potential customers for this app are medical professionals that need to scale and improve the accuracy of their diagnoses using AI. From ideation, to logo design, to integrating features like payments and AI into a single app, I'll show you my 10 step process. I hope that by seeing my thought process and getting familiar with the sequence of steps I'll demonstrate,, you too will be as inspired as I am to use this technology to do something great for the world. Enjoy! Code for this video: https://github.com/llSourcell/AI_Startup_Prototype Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval More Learning resources: https://www.youtube.com/watch?v=FTr3n7uBIuE https://www.youtube.com/watch?v=9bbS-trc8ys&t=608s https://www.youtube.com/watch?v=mrRfpiAwad0 https://www.youtube.com/watch?v=HhqhFbwiaig&t=563s Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Hit the Join button above to sign up to become a member of my channel for access to exclusive live streams! Join us at the School of AI: https://theschool.ai/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w And please support me on Patreon: https://www.patreon.com/user?u=3191693

Natural Language Processing is a field of Artificial Intelligence dedicated to enabling computers to understand and communicate in human language. NLP is only a few decades old, but we've made significant progress in that time. I'll cover how its changed over the years, then show you how you can easily build an NLP app that can either classify or summarize text. This is incredibly powerful technology that anyone can freely use, I'll show you how to do it. Enjoy! Code for this video: https://github.com/llSourcell/bert-as-service Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval More Learning resources: https://www.youtube.com/watch?v=0n95f-eqZdw http://mlexplained.com/2019/01/30/an-in-depth-tutorial-to-allennlp-from-basics-to-elmo-and-bert/ https://towardsdatascience.com/beyond-word-embeddings-part-2-word-vectors-nlp-modeling-from-bow-to-bert-4ebd4711d0ec https://gluon-nlp.mxnet.io/examples/sentence_embedding/bert.html Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Join us at the School of AI: https://theschool.ai/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

Nvidia is the inventor of the GPU! This tech company based in Silicon Valley has played a huge role in the deep learning revolution (which has relied primarily on GPUs for computing), and its transformed many industries. In this video, I interview Bryan Catanzaro, the Vice President of Applied Deep Learning Research at NVIDIA. Bryan got his PhD in AI from Berkeley, invented a language called Copperhead, and is an expert in parallel programming theory. Nvidia invited me to their annual conference, so I took the opportunity to ask Bryan 67 questions while walking through the halls. Enjoy! Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval More Learning resources: https://ctnzr.io/ https://developer.nvidia.com/deep-learning https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3 https://www.youtube.com/watch?v=Cr6VqTRO1v0&t=342s Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Join us at the School of AI: https://theschool.ai/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

Discrete Math is a subject everyone interested in Computer Science needs to understand. It consists of math branches like graph theory, set theory, number theory, & combinatorics. It helps create databases, algorithms, & security structures. In this video, I'll explain the most relevant topics in Discrete Math one by one as we try to decrypt the password for a SQL database. Along the way, we'll use discrete math in various ways. I wanted to see if I could summarize an important course I took in college in a single video. Enjoy! Code for this video: https://github.com/llSourcell/DiscreteMath Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: http://discrete.openmathbooks.org/home.php https://cse.buffalo.edu/~rapaport/191/S09/whatisdiscmath.html https://www.cs.odu.edu/~toida/nerzic/content/intro2discrete/intro2discrete.html https://www.youtube.com/watch?v=YzfdL58virc Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

I recently flew to Singapore to give a keynote on AI in healthcare and attend a panel discussion on the same topic hosted by School of AI and sponsored by Accenture. School of AI is a nonprofit with a goal of giving everyone on Earth a world-class AI education for free. This was a launch event for our first global hackathon called Health Hack that will be hosted in over 30 cities around the world by our Deans (community representatives). In this video, you'll learn about automated diagnostics, synthetic biology, drug discovery, and the ethical implications of AI. Enjoy! Link to the hackathon (RSVP at the city closest to you if there is one): https://www.theschool.ai/hackathon/ Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://www.youtube.com/watch?v=DCcmFXXAHf4&t=248s https://www.youtube.com/watch?v=hY9Bc3mtphs&t=462s https://rockhealth.com/reports/demystifying-ai-and-machine-learning-in-healthcare/ https://healthcare.ai/ https://www.nvidia.com/en-us/deep-learning-ai/industries/healthcare/ Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

Unsupervised learning is the most exciting subfield of machine learning! Finding structure in unstructured data automatically sounds like a dream come true, no need to have a label! In this video, I'll demonstrate 2 types of unsupervised learning techniques; k means clustering and principal component analysis. We'll use these techniques on neural data from a patient suffering from seizures to see if we can locate the part of their brain in need of surgery to save their life. You'll laugh, you'll cry, but most importantly, you'll learn. Enjoy! Code for this video: https://github.com/llSourcell/spike_sorting Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://blog.algorithmia.com/introduction-to-unsupervised-learning/ http://deeplearning.stanford.edu/tutorial/ https://towardsdatascience.com/unsupervised-learning-with-python-173c51dc7f03 https://medium.com/machine-learning-for-humans/unsupervised-learning-f45587588294 Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

Is it possible to use machine learning without needing to code? The answer is yes! Uber's AI lab recently open sourced python library called Ludwig that they've been using internally for 2 years. The tagline is that it allows anyone to use deep learning without coding. It will require some configuration and unix commands to setup, but I'll show you how in this video. I'll also talk about other code-free tools like Azure ML Studio, DataRobot, and DeepCognition. Enjoy! Code for this video: https://github.com/llSourcell/ludwig Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://uber.github.io/ludwig/ https://azure.microsoft.com/en-us/services/machine-learning-studio/ https://www.datarobot.com/ https://deepcognition.ai/ Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content! #MachineLearning #SirajRaval

The AI research lab DeepMind created an algorithm that beat a top professional StarCraft 2 player for the first time! This is a huge achievement since this is an incredibly complex game that requires long term planning, game theory, and cooperative play. Their algorithm used a mixture of techniques that in the field of deep reinforcement learning. I'll explain how each of these techniques works, and how they all work together in unison. This is an exciting time for the field. Enjoy! Code for this video: https://github.com/llSourcell/pysc2 Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://deepmind.com/blog/alphastar-mastering-real-time-strategy-game-starcraft-ii/ https://www.vox.com/future-perfect/2019/1/24/18196177/ai-artificial-intelligence-google-deepmind-starcraft-game https://medium.freecodecamp.org/an-intro-to-advantage-actor-critic-methods-lets-play-sonic-the-hedgehog-86d6240171d http://www.dcsc.tudelft.nl/~bdeschutter/pub/rep/10_003.pdf Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

OpenAI has the entire AI community debating its decision to not release the fully trained version of its powerful new text generator model dubbed GPT-2. I'm going to explain how GPT-2 works using code, math, and animations. We'll discuss its potential applications (both good and bad), ways of preventing misuse, and at the end of the video I'll give my take on whether OpenAI was justified in doing so. The transformer architecture is quickly replacing recurrent networks for sequence learning, and OpenAI's GPT-2 is the latest example of using it at scale. Enjoy! Code for this video: https://github.com/openai/gpt-2 Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://medium.com/@asierarranz/i-have-created-a-website-to-query-the-gpt-2-openai-model-11dd30e1c8b0 https://blog.openai.com/better-language-models/ http://jalammar.github.io/illustrated-transformer/ https://mchromiak.github.io/articles/2017/Sep/12/Transformer-Attention-is-all-you-need/#.XHVUts9KiLI Web Demo of GPT-2: https://www.askskynet.com/ Gradient Descent: https://www.youtube.com/watch?v=XdM6ER7zTLk&t=774s Fakebox: https://machinebox.io/docs/fakebox Privacy tools: https://github.com/OpenMined/PySyft/tree/master/examples/tutorials Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

Data Science coding challenge time! The popular Data Science competition website Kaggle has an ongoing competition to solve the problem of earthquake prediction. Given a dataset of seismographic activity from a laboratory simulation, participants are asked to create a predictive model for earthquakes. In this video, I'll attempt the challenge as a way to teach 3 concepts; the Data Science mindset, Categorical Boosting, and Support Vector Regression models. I'll be coding this using python from start to finish in the online Google colab environment. Enjoy! Code for this video: https://github.com/llSourcell/Kaggle_Earthquake_challenge Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology Join us at the School of AI: https://theschool.ai/ More learning resources: https://www.kaggle.com/c/LANL-Earthquake-Prediction/data https://www.analyticsvidhya.com/blog/2017/08/catboost-automated-categorical-data/ https://blog.griddynamics.com/xgboost-vs-catboost-vs-lightgbm-which-is-best-for-price-prediction/ https://towardsdatascience.com/catboost-vs-light-gbm-vs-xgboost-5f93620723db https://accio.github.io/machinelearning/2018/05/30/catboost.html http://kernelsvm.tripod.com/ https://www.saedsayad.com/support_vector_machine_reg.htm https://medium.com/coinmonks/support-vector-regression-or-svr-8eb3acf6d0ff https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

Everyone needs to understand regression! Its a useful data science technique that allows us to understand the relationship between different variables. In this video, we'll play the role of a newly hired data analyst at a genetics company trying to find the relationship between advertising mediums (TV, newspaper, radio) and ticket sales to our newly opened theme park. Along the way, we'll learn about 5 types of regression models (linear, non-linear, multiple, lasso, and ridge). Expect math, code, and layers of explanation. Enjoy! Code for this video: https://github.com/llSourcell/ISL-Ridge-Lasso Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://www.youtube.com/watch?v=XdM6ER7zTLk https://www.analyticsvidhya.com/blog/2017/06/a-comprehensive-guide-for-linear-ridge-and-lasso-regression/ http://statisticsbyjim.com/regression/choose-linear-nonlinear-regression/ https://hbr.org/2015/11/a-refresher-on-regression-analysis http://blog.minitab.com/blog/adventures-in-statistics-2/how-to-interpret-regression-analysis-results-p-values-and-coefficients Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

There are so many different ways to visualize data! We're going to learn about the major types of visualizations (relationships, correlations, comparisons) as well as discuss some of the many powerful visualization tools that are available to us. Google Charts, Tableau, there are a lot! We'll break down the visualization process along many dimensions, revealing the subtleties that can make or break a chart. Using the plotly library. we'll visualize a Medium blog post dataset many different ways. Enjoy! Code for this video: https://github.com/llSourcell/Data_Visualization Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology Join us at the School of AI: https://theschool.ai/ More learning resources: https://medium.com/@Infogram/18-data-visualization-resources-for-education-and-inspiration-529c6f528983 https://machinelearningmastery.com/data-visualization-methods-in-python/ http://newcoder.io/dataviz/intro/ https://www.kaggle.com/benhamner/python-data-visualizations https://towardsdatascience.com/data-science-with-python-intro-to-data-visualization-and-matplotlib-5f799b7c6d82 https://realpython.com/python-data-visualization-bokeh/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

Statistics is crucial to Data Science! In fact, the phrase Data Science was first used in a Statistics conference title. In this video, I'll cover 3 key concepts from Statistics that every Data Scientist needs to know. Statistical features, probability distributions, and Bayesian statistics will be explained using code, theory, and animations. Our specific application will be finding an optimal credit score for someone using Lending Club's loan data. Expect a musical interlude. Enjoy! Code for this video: https://github.com/llSourcell/LoanDefault-Prediction Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology Join us at the School of AI: https://theschool.ai/ More learning resources: https://www.kdnuggets.com/2018/12/introduction-statistics-data-science.html https://towardsdatascience.com/the-5-basic-statistics-concepts-data-scientists-need-to-know-2c96740377ae https://www.kdnuggets.com/2017/11/10-statistical-techniques-data-scientists-need-master.html https://www.learndatasci.com/tutorials/data-science-statistics-using-python/ https://towardsdatascience.com/probability-and-statistics-explained-in-the-context-of-deep-learning-ed1509b2eb3f https://www.datascience.com/blog/statistics-data-science-interview https://www.datasciencecentral.com/profiles/blogs/29-statistical-concepts-explained-in-simple-english-part-1 Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

This past week Kaggle invited me to attend an event they hosted called Kaggle Days in Paris, France. Kaggle Days are a global series of offline events for seasoned data scientists and Kagglers. It was a lot of fun! I met some really interesting people from all over the world and the venue they booked is the biggest startup campus in the world (Station F). In this video, I'll introduce Kaggle Days, interview 5 top data scientists, and conclude with a demo from a top Kaggler on inventory prediction. Enjoy! Code for this video: https://github.com/llSourcell/invent-prediction Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://kaggledays.com/ https://www.youtube.com/watch?v=suRd3UzdBeo https://www.youtube.com/watch?v=P1lgTATSVYA Join us at the School of AI: https://theschool.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w

Welcome to Data Lit! This 3 month course is an intro to data science for beginners. In this video, i'll explain how a popular data science technique called sentiment analysis works using a real-world scenario. We'll play the role of a data scientist working at a startup making a personal healthcare device. Using sentiment analysis, we'll understand how consumers feel about a competitors product. That'll help us make decisions on how to promote our own product, and what feature we can focus on the most. Using Python, Twitter, and Google Colab, anyone can do this process in just a few minutes. Enjoy! Code for this video: https://github.com/llSourcell/Sentiment_Analysis Please Subscribe! And Like. And comment. Thats what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology Join us at the School of AI: https://theschool.ai/ More learning resources: https://towardsdatascience.com/sentiment-analysis-with-python-part-1-5ce197074184 https://www.geeksforgeeks.org/twitter-sentiment-analysis-using-python/ https://www.datacamp.com/community/tutorials/simplifying-sentiment-analysis-python https://www.kaggle.com/ngyptr/python-nltk-sentiment-analysis https://pythonspot.com/python-sentiment-analysis/ https://www.analyticsvidhya.com/blog/2018/07/hands-on-sentiment-analysis-dataset-python/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w