Piers Stobbs’ Post

Our May newsletter is out- lots of great AI and data science research, posts and tutorials- hope you enjoy it! https://lnkd.in/edcy9F7N #datascience #ai #machinelearning

Very interesting articles in this month's Royal Statistical Society newsletter. I especially liked Wharton's new product innovation study on 'Ideas Are Dimes A Dozen: Large Language Models For Idea Generation In Innovation'. "We have not produced evidence that ChatGPT is better than the best human product innovators working today. However, we believe that we can claim conservatively that ChatGPT is better than many human product innovators working today and probably better than average. Thus, at a very minimum, an LLM could elevate the least capable humans to a better-than-average level of performance" https://lnkd.in/ezqAQpFr Give the prompt a try, and maybe you will start a new career as an entrepreneur? "You are a creative entrepreneur looking to generate new product ideas. The product will target college students in the United States. It should be a physical good, not a service or software. I'd like a product that could be sold at a retail price of less than about USD 50. The ideas are just ideas. The product need not yet exist, nor may it necessarily be clearly feasible. Number all ideas and give them a name. The name and idea are separated by a colon. Please generate ten ideas as ten separate paragraphs. The idea should be expressed as a paragraph of 40-80 words. Temperature = 0.7" Piers Stobbs #innovation #productmanagement

Starting soon with pre-bootcamp live training, the ODSC West Bootcamp program has everything you need to get started with data science and AI. #DataScience #ArtificialIntelligence https://hubs.li/Q01_hgtR0

Starting soon with pre-bootcamp live training, the ODSC West Bootcamp program has everything you need to get started with data science and AI. #DataScience #ArtificialIntelligence https://hubs.li/Q01_hply0

- AI of the day - [46] “”” 100 Applications of Generative AI “”” It's packed with innovative uses of generative AI across various industries, from art and design to healthcare and finance. Whether you're a seasoned data scientist or just dipping your toes into the world of AI. #GenerativeAI #DataScience #ArtificialIntelligence #Innovation #ArtificialIntelligence #Robotics #Innovation #TechAdvancements #Productivity #AITools #OpenSourceAI #Innovation #Collaboration #AICommunity #smartercities #smartercountries #tom2200 #thailandonmars2200 #THtransformation4nextcentury #masterplanfordevelopingcountry be —> Original | Professional | Legacy <—

Learn about Taylor's experience with our Data Science Bootcamp and why he recommends it for beginners. Learn how you can kickstart your data science career with our bootcamp: https://hubs.la/Q01-rjzP0 #DataScience #AI ##Bootcamp

 Exciting Day 28 at the 6-month Data Science and AI BootCamp at Codanics with Dr. Muhammad Aammar Tufail! 🚀 Today's topic is #featurescaling and #featureencoding. Let's dive in and explore these essential concepts in data science! 💡 ⚙️ Feature scaling is a crucial step in data preprocessing. It helps us bring all our features to a consistent scale, ensuring no single feature dominates the others. This normalization process enhances the performance of many machine-learning algorithms. 📊 📌 Feature encoding is a technique used to convert categorical variables into numerical representations that machine learning models can understand. It helps us unlock the potential of categorical data in our analysis and predictions. 🗂️ During today's session, we learned the following key points: ✅ Feature Scaling: - Methods to Feature Scale data with their mathematical formulas. - Standardization: Transforming data with a mean of 0 and a standard deviation of 1. - Normalization: Scaling data to a range of 0 to 1. - Benefits: Improved model performance, faster convergence, and preventing features with larger values from dominating. ✅ Feature Encoding: - Some important methods of Feature Encoding: 1. One-Hot Encoding: Creating binary columns for each category, representing their presence or absence. 2. Label Encoding: Assigning unique numerical labels to each category. 3. Ordinal Encoding: Converts data into meaningful orders. - Benefits: Enabling algorithms to work with categorical data, preserving valuable information, and reducing dimensionality. By mastering these techniques, we can enhance our data analysis and model-building skills, leading to more accurate predictions and valuable insights. 🔍💪 📚 Stay tuned for tomorrow's session, where we'll explore even more exciting concepts in the world of data science and AI! 🌟 #data #datascience #dataanalytics #datascientist #ai #machinelearning #bootcamp #dataanalysis #dataanalyst #eda #datapreprocessing

Andrew Ng will be speaking at 서울대학교 (Seoul National University) on July 20th for Data Science Day! This event commemorates the opening of the "Center for Huge AI Models and Platforms Optimization (CHAMP)." Event info: https://bit.ly/3JY3AaI #DataCentricAI #DataScience #AI

Uncover our top 3 #AI & #ML announcements from last week's #Snowday event by Snowflake from our Chief Architect of Machine Learning & Data Science, Dominick Rocco 🔥 What announcements are you most excited for? For more coverage of Snowday, check out our full write-up that explores all of the major updates and more! 👇 https://lnkd.in/eZNn9pnh #artificialintelligence #machinelearning #snowflakedatacloud