Apple's Health App: A Better Wellness | Shelly Palmer on Fox 5

Shelly Palmer discusses Apple’s iOS Health App with Sukanya Krishnan and Jennifer Lahmers on Fox 5’s Good Day Wake Up. Original Air Date: October 9, 2018

Continue reading “Apple's Health App: A Better Wellness | Shelly Palmer on Fox 5”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

AI in 2040

What does the field of Artificial Intelligence look like in 2040? It’s a really hard question to answer since there are still so many unanswered questions about the nature of reality and computing. In this episode, I’ll make my best predictions about AI hardware, AI software, and the societal impact of AI in 2040. We’ll cover quantum mechanics, neuromorphic computing, DNA storage, decentralized computing, basic income, and mind-body machines. Enjoy! Code for this video: https://github.com/llSourcell/quantum_machine_learning_LIVE/blob/master/Demo.ipynb 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:// instagram: https://

Continue reading “AI in 2040”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

How to Make a Text Summarizer – Intro to Deep Learning #10

I’ll show you how you can turn an article into a one-sentence summary in Python with the Keras machine learning library. We’ll go over word embeddings, encoder-decoder architecture, and the role of attention in learning theory. Code for this video (Challenge included): https://github.com/llSourcell/How_to_make_a_text_summarizer Jie’s Winning Code: https://github.com/jiexunsee/rudimentary-ai-composer More Learning resources: https:// https://research.googleblog.com/2016/08/text-summarization-with-tensorflow.html https://en.wikipedia.org/wiki/Automatic_summarization

Continue reading “How to Make a Text Summarizer – Intro to Deep Learning #10”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

E887 #StartupTuneup: teledentistry, cannabis tax, activewear bras, data science, 3D printing, travel

SIGN UP FOR TWIST EPISODES MAILING LIST: E887: #StartupTuneup @ TWiST Live! Jason’s candid feedback to founders on teledentistry as a service, tax management for cannabis, stylish activewear bras, data science for software engineering, online 3D printing, integrated traveling platform Follow us on… Twitter: Jason’s Twitter: LAUNCH Twitter: Instagram: Jason’s Instagam: LAUNCH Instagram: Connect with Jason on LinkedIn: https://linkedin.com/in/jasoncalacanis/ Show notes: 0:50 – Jason introduces LAUNCH and what they’re doing to help founders. 6:06 – Pitches from Darryl Davis from Rockridge

Continue reading “E887 #StartupTuneup: teledentistry, cannabis tax, activewear bras, data science, 3D printing, travel”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

Kaggle Challenge (LIVE)

Two Sigma Investments published a $100,000 code competition on Kaggle that asks data scientists around the world to try their best to create an algorithm that can make predictions about anonymous financial instruments (like derivatives, assets, bonds). Normally, reinforcement learning is not used on Kaggle but in this live stream I’ll use reinforcement learning to help solve this challenge. This will serve as a great real-world use case for RL and I’ll also discuss some other common time series forecasting methods. Get hype! Code for this video: https://github.com/llSourcell/Kaggle_Challenge_LIVE-Two-Sigma Dataset: https:// Please Subscribe! And like. And comment. That’s what keeps me going. Want more education? Conne

Continue reading “Kaggle Challenge (LIVE)”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

Web Scraping and Parsing | Retrieving Tags with Beautiful Soup in Python – Tutorial 35 in Anaconda

In this Python for Data Science Tutorial, You will learn about Parsing Data In Python, Searching and Retrieving Data in Python, Filtering Data. How to Get Data From a Parse Tree using Beautiful Soup. You will Learn how to retrieve tags using filtering with name arguments, how to retrieve tags using filtering with keyword arguments, and with string arguments. and with list objects. This is the 35th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebook

Continue reading “Web Scraping and Parsing | Retrieving Tags with Beautiful Soup in Python – Tutorial 35 in Anaconda”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

Lecture 43 — Part of Speech Tagging – Natural Language Processing | Michigan

. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “FAIR USE” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .

Continue reading “Lecture 43 — Part of Speech Tagging – Natural Language Processing | Michigan”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

How to Predict Stock Prices Easily – Intro to Deep Learning #7

We’re going to predict the closing price of the S&P 500 using a special type of recurrent neural network called an LSTM network. I’ll explain why we use recurrent nets for time series data, and why LSTMs boost our network’s memory power. Coding challenge for this video: https://github.com/llSourcell/How-to-Predict-Stock-Prices-Easily-Demo Vishal’s winning code: https://github.com/erilyth/DeepLearning-SirajologyChallenges/tree/master/Image_Classifier Jie’s runner up code: https://github.com/jiexunsee/Simple-Inception-Transfer-Learning More Learning Resources: https://deeplearning4j.org/lstm.html https://

Continue reading “How to Predict Stock Prices Easily – Intro to Deep Learning #7”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

Trading the Market With Conditional Probabilities | Data Science Lab

Does the market have a “memory?” If there are three “up days” in a row, what is the probability of a fourth “up day?” Find out! See more options trading videos: Understanding the probabilities in options trading is crucial to tastytrade mechanics. Today, Mike Rechenthin (known as Dr. Data) uses his PhD in Management Sciences to determine the probability of a fourth up day in the market after three consecutive previous up days. Using Bayes’ Theorem and over 65 Years of S&P 500 data, the probability of a “4th up day, given 3 consecutive up days” is 53.1%. What’s especially interesting is that we found the probability of a 5th consecutive up day or a 6th or a 7th is all around 53%. Which is the same probability of having a “normal” up day, not conditional on a

Continue reading “Trading the Market With Conditional Probabilities | Data Science Lab”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page

R – Sentiment Analysis and Wordcloud from Twitter Data with R | Example using Apple Tweets

Link to R and csv files: https://drive.google.com/open?id=0B5W8CO0Gb2GGWGtyZHlLWG1oR2s https://drive.google.com/open?id=0B5W8CO0Gb2GGTEs3SUZ0Qnp3Mms https://drive.google.com/open?id=0B5W8CO0Gb2GGTFZCbkdqTUdCV0E Provides sentiment analysis and steps for making word clouds with r using tweets about apple obtained from Twitter. Topics include: – reading data obtained from Twitter in a csv format – cleaning tweets for further analysis – creating term document matrix – making wordcloud, lettercloud, and barplots – sentiment analysis of apple tweets before and after quarterly earnings report R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets p

Continue reading “R – Sentiment Analysis and Wordcloud from Twitter Data with R | Example using Apple Tweets”

It's only fair to share...Tweet about this on TwitterShare on FacebookShare on TumblrShare on Google+Digg thisShare on LinkedInPin on PinterestShare on VKShare on RedditPrint this pageEmail this to someone
Flattr the authorShare on StumbleUponShare on YummlyBuffer this page