Data Science Demonstrated
Data Science Demonstrated
  • Видео 87
  • Просмотров 116 559
Enhance shopping experience with Generative AI Chat-powered E-commerce
With the advent of generative AI, we now have the opportunity for chat-powered interface to shopping. See how this new approach can provide a more natural, conversational way to purchase products, enhancing the overall shopping experience.
Try out the demo at experiencedatascience.com
Просмотров: 39

Видео

AI's Most Powerful Capability Yet : Multi-Modal AI with Reasoning Demonstrated
Просмотров 63Месяц назад
See a demo on multi-modal AI with reasoning - a very powerful way to leverage AI Demo available at experiencedatascience.com
Analyse the pattern of an iconic speech and then use it to make your own speech iconic !
Просмотров 53Месяц назад
Analyzing Iconic Speeches with AI: Understand the pattern and then use it to make your speech iconic. In this video, you will see a demo of analysing Steeve job iphone launch speech You can try out the demo at experiencedatascience.com
Amazing speech to text using Open.AI Whisper: Use-cases and DEMO
Просмотров 862 месяца назад
See an exciting demo of speech to text conversion . You can try out the demo at experiencedatascience.com
See fascinating demo for e-commerce: Generate AI-Images from product description
Просмотров 1292 месяца назад
Text-to-image generation leverages advanced artificial intelligence to create visually rich, contextually relevant imagery from simple textual descriptions. See a demo on how to convert product description to images which can be very useful in e-commerce and fashion industry Try out the demo at experiencedatascience.com
How to create data stories with DATA + MUSIC + VIDEO !!!
Просмотров 992 месяца назад
Step into the future of data story with Generative AI. In this video I will show you how a 100% AI generated data story which used AI generated music, video, images and analysis. The following tools are used Hugging face:huggingface.co/ OpenAI SORA: openai.com/index/sora/ ChatGPT: chatgpt.com/ Experience data science: experiencedatascience.com The Kaggle space titanic problem is described here ...
Does Generative AI means end of traditional machine learning ?
Просмотров 2593 месяца назад
Generative AI is fast changing everything including how we do machine learning. The new way of doing machine learning will definitely help boost data science productivity In this video I will comparision traditional machine learning vs Generative AI This video will provide key insights into the future direction of AI and help you prepare for what's coming Try out a demo on sentiment analysis on...
EPIC! Thank you for 100K Views ! Watch the 100K Race !
Просмотров 613 месяца назад
I would like to thank all my subscribers and viewers for making my channel reach 100K View In this video, you will see an animated Racing Bachart which will show which are the top videos which contributed to 100K. The race is tight ! If you are interested in making racing barchart without coding, you can do it on my platform experiencedatascience.com Top video to win the epic race -Dynamic Pric...
Dynamic Pricing with Generative AI : A radically innovative approach !
Просмотров 8933 месяца назад
Dynamic pricing is nowadays used in many applications such as booking a taxi, or booking a hotel or selling online products. In dynamic pricing, the price is not fixed, but determined in various factors. See how to use Generative AI for dynamic pricing. Try out the demo at experiencedatascience.com Also see Dynamic Pricing with Machine learning - ruclips.net/video/ZtWzEbytBkI/видео.htmlfeature=...
Cricket commentary analytics with Generative AI - A must watch for cricketing fans!
Просмотров 4323 месяца назад
Immerse yourself into cricket sports moments by analzing commentary data using Generative AI ! Try out the demo at experiencedatascience.com. !
Time Series Missing Value Prediction - A visual demo
Просмотров 613 месяца назад
All data suffer from missing values and time series data is no exception. In this experience, you will see how to replace missing values in time series data using the very useful key nearest neighbor algorithm Try out the demo - experiencedatascience.com 00:00 Inttroduction 00:40 Missing data 02:54 Line chart analysis 03:38 Missing value analysis 04:18 KNN
Machine learning tactic - See it in action with a demo
Просмотров 694 месяца назад
Tactic , is sequence of actions, aiming to achieve a certain goal. It can help deciding an approach to a solve machine learning problem and avoid to directly jump to algorithms. See it in action by solving famous data science problem of spaceship titanic Try out the demo at - experiencedatascience.com 00:00 Introduction 01:09 The Problem 01:51 Data Exploration 06:16 Tactic to solve the problem ...
Hierarchical Clustering is more than just visuals - See a very practical python demo
Просмотров 1384 месяца назад
See a very practical demo of Hierarchical Clustering in python You can try out the demo and get the code at experiencedatascience.com You will find the Hierarchical Clustering experience on first page of the website or see all experiences-Data science and data analysis
5 Reasons why Hierarchical Clustering is awesome !
Просмотров 1745 месяцев назад
Discover the 5 Reasons why Hierarchical Clustering is awesome ! Demo available at experiencedatascience.com
Create powerful Knowledge Graph from Text Data
Просмотров 1395 месяцев назад
Create powerful Knowledge Graph from Text Data. Try out the demo at experiencedatascience.com
Q&A with Text Data: A fascinating Gen AI Demo
Просмотров 1326 месяцев назад
Q&A with Text Data: A fascinating Gen AI Demo
Create powerful machine learning models with these golden rules
Просмотров 786 месяцев назад
Create powerful machine learning models with these golden rules
Demo Text Classification / Tagging with OPEN.AI
Просмотров 3847 месяцев назад
Demo Text Classification / Tagging with OPEN.AI
Web Scraping + Text Analytic on world's largest AI model website ! (huggingface)
Просмотров 3997 месяцев назад
Web Scraping Text Analytic on world's largest AI model website ! (huggingface)
Most comprehensive demo of outlier detection algorithms
Просмотров 2547 месяцев назад
Most comprehensive demo of outlier detection algorithms
How telco's monitor network quality - a data analytics demo
Просмотров 848 месяцев назад
How telco's monitor network quality - a data analytics demo
[Travel Hack] Discover the Shortest Path to Explore the Entire Globe!
Просмотров 1028 месяцев назад
[Travel Hack] Discover the Shortest Path to Explore the Entire Globe!
DEMO: Power of Text Summarisation using OpenAI
Просмотров 1219 месяцев назад
DEMO: Power of Text Summarisation using OpenAI
Is it worth paying $24/month to use ChatGPT Plus for data analysis
Просмотров 2119 месяцев назад
Is it worth paying $24/month to use ChatGPT Plus for data analysis
What 's under ChatGPT's hood ? Deep learning Transformer Architecture Visually Explained
Просмотров 3569 месяцев назад
What 's under ChatGPT's hood ? Deep learning Transformer Architecture Visually Explained
Thank you for 2K subscribers !!!
Просмотров 1029 месяцев назад
Thank you for 2K subscribers !!!
Product Recommendation using a Language Model using deep learning - A Visual Demo
Просмотров 21610 месяцев назад
Product Recommendation using a Language Model using deep learning - A Visual Demo
Sentiment Analysis with Hugging face - A VISUAL DEMO
Просмотров 32910 месяцев назад
Sentiment Analysis with Hugging face - A VISUAL DEMO
Maximizing Profits: Market Basket Analysis Explained & Demonstrated
Просмотров 26111 месяцев назад
Maximizing Profits: Market Basket Analysis Explained & Demonstrated
Sentiment Analysis with Open.AI - A VISUAL DEMO
Просмотров 1,2 тыс.Год назад
Sentiment Analysis with Open.AI - A VISUAL DEMO

Комментарии

  • @JunaidAhmed-jd5kq
    @JunaidAhmed-jd5kq 3 дня назад

    Hey, Where can I get this dataset?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 3 дня назад

      @@JunaidAhmed-jd5kq Hi, you can get it from here www.kaggle.com/c/mercari-price-suggestion-challenge

  • @emilymyers9676
    @emilymyers9676 26 дней назад

    Interesting!

  • @Amankumar-iv4er
    @Amankumar-iv4er Месяц назад

    A perfect example of a GOOD TEACHER

  • @emilymyers9676
    @emilymyers9676 Месяц назад

    Very cutting-edge !

  • @user-wr4yl7tx3w
    @user-wr4yl7tx3w 2 месяца назад

    Is it free to use whisper?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 2 месяца назад

      Hi, The Whisper API is not free . However it’s does a very good job, so it’s worth

  • @martink20118
    @martink20118 2 месяца назад

    Interesting demo but forgive me I isn’t it just a fancy “look up” table ? I mean the predicted price is just checking if a descriptor is im a table or not and then applying a price accordingly? Apologies if I’ve missed the insight here. Appreciate any clarification cheers

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 2 месяца назад

      Hi, Thanks for your comment. The look up table technique does not work as the items which are put in sale have a description which is given by a seller in free-form. Every item description is generally unique even if it’s the an identical product. Also sellers put many specific things and personalize the description. So the exact description in not available in past sales . Hence it’s required to use a LLM approach Hope this helps . Thanks for watching my channel

    • @martink20118
      @martink20118 2 месяца назад

      @@DataScienceDemonstrated yes thanks - i missed that point....i'd better watch the video in full :)

  • @faisalIqbal_AI
    @faisalIqbal_AI 3 месяца назад

    Very informative

  • @KA00_7
    @KA00_7 3 месяца назад

    amazing. its super helpful video.please upload more more video like this.

  • @BronzeYohn
    @BronzeYohn 3 месяца назад

    I can see using LLMs to establish better embeddings to run the traditional pricing algo's (time-series, regression, decision-trees off), but it's not going to give you optimised elasticities on its own. Unless I'm grossly mistaken.

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 3 месяца назад

      Good point. LLM approach is useful when price depends on text description, which is relevant for market place scenarios

  • @emilymyers9676
    @emilymyers9676 3 месяца назад

    This is Epic !

  • @emilymyers9676
    @emilymyers9676 3 месяца назад

    Very innovative indeed ! Thanks for creating this video

  • @karunakarbhoga2092
    @karunakarbhoga2092 3 месяца назад

    awesome different customer analysis and visuals explained and also very efficient way explained

  • @subhrobose5149
    @subhrobose5149 3 месяца назад

    Very good sir

  • @DataScienceDemonstrated
    @DataScienceDemonstrated 3 месяца назад

    What is your favorite Generative AI technique to analyze sporting moments ?

  • @jeanmarcel6131
    @jeanmarcel6131 3 месяца назад

    This is great ! Now I am getting interested in cricket !

  • @shadeersadikeen1052
    @shadeersadikeen1052 3 месяца назад

    Can you share the source code to. how to build a smart pricing model. because there is no video can be found in the youtube =.

  • @n.adityakrishnanneelakanta9083
    @n.adityakrishnanneelakanta9083 4 месяца назад

    source code of the project

  • @yusmanisleidissotolongo4433
    @yusmanisleidissotolongo4433 5 месяцев назад

    Fantastic. This is great presentation that helps learners.

  • @MrEmptyfuel
    @MrEmptyfuel 5 месяцев назад

    Best customer analytics video ever

  • @anishbhanushali
    @anishbhanushali 5 месяцев назад

    the parameters of openAI model could be way higher than open-source bert model makes this comparison not apples to apples in a way.

  • @anupgeorge2261
    @anupgeorge2261 6 месяцев назад

    Excellent useful

  • @emilymyers9676
    @emilymyers9676 6 месяцев назад

    Really fascinating !

  • @emilymyers9676
    @emilymyers9676 6 месяцев назад

    Nicely explained !

  • @aparnakanchan5147
    @aparnakanchan5147 6 месяцев назад

    Very well explained! Thank you and keep it coming:)

  • @kennethstephani692
    @kennethstephani692 6 месяцев назад

    Great video!

  • @emilianogd7613
    @emilianogd7613 6 месяцев назад

    Hi, I can't fin this project on your website, could you help me?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 6 месяцев назад

      Hi, once you are on my website (experiencedatascience.com/), please login. Once you are logged in, go to See All Experiences. Then select Data science and data analysis. Then you will see the "Health Activity Analysis" which corresponds to the project in the video. Let me know for any questions. Thanks

  • @rrrfamilyrashriderockers6891
    @rrrfamilyrashriderockers6891 6 месяцев назад

    very interesting can you share github code

  • @ArenitaHernandez
    @ArenitaHernandez 6 месяцев назад

    Thank you!🎉

  • @emilymyers9676
    @emilymyers9676 7 месяцев назад

    Very cool

  • @jeanmarcel6131
    @jeanmarcel6131 7 месяцев назад

    Awesome!

  • @corren5349
    @corren5349 7 месяцев назад

    Promo`SM

  • @user-jj3we9jv9i
    @user-jj3we9jv9i 8 месяцев назад

    Good job!

  • @jeanmarcel6131
    @jeanmarcel6131 8 месяцев назад

    Awesome !

  • @jeanmarcel6131
    @jeanmarcel6131 9 месяцев назад

    Nice !

  • @omerdavid9673
    @omerdavid9673 9 месяцев назад

    Good job I liked the demonstration, I think you should further explain the hyperparameter tuning in dbscan because it can drastically change the results

  • @user-ul8uy9xy4d
    @user-ul8uy9xy4d 9 месяцев назад

    Hi sir, I didn't really understand the cluster analysis - what are the different colours, what is the trend, what do the different colours represent? Thank you!

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 9 месяцев назад

      Hi, the cluster groups similar reviews together. The colors signify reviews of similar products. For example at 1:51, the red cluster on top left of the screen is related to dog food

  • @abdulbasitbello2381
    @abdulbasitbello2381 9 месяцев назад

    I love your videos! Thank you for making these 🙏

  • @jeanmarcel6131
    @jeanmarcel6131 9 месяцев назад

    Excellent explanation! Thanks

  • @samannwaysil4412
    @samannwaysil4412 9 месяцев назад

    Please try to enhance your audio quality.

  • @steversmith1
    @steversmith1 9 месяцев назад

    I can't find the example on your website.

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 9 месяцев назад

      Hi, Let me check. In the meantime, you can also do same analytics as follows - 1. Use menu Datasets-Play Datasets to copy taxi_data_porto_location dataset. 2. Then select Datasets-Your Datasets, select the taxi_data_porto_location, and select Analytics. You will see all analytics including histogram, boxplot, geolocation etc..

  • @517127
    @517127 9 месяцев назад

    And How can we optimize this price ?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 9 месяцев назад

      Hi, you will need demand data , which can be as an input feature to your model. The output price is optimized based on the demand

  • @upskillwithchetan
    @upskillwithchetan 10 месяцев назад

    Awesome 🎉

  • @jeromeeusebius
    @jeromeeusebius 10 месяцев назад

    Thanks for the video. In the 2-dimensional plot, we have reduced the 1540 vectors to a 2-d in-order to be able to plot them. Which algorithm did you for this reduction? t-SNE, UMAP, or some other algorithm.

  • @sankalpsingh1359
    @sankalpsingh1359 11 месяцев назад

    Can you please specify how you made the plots, specifically radarplot or give its source code?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 10 месяцев назад

      Hi, I used Javascript library ECharts. See this link echarts.apache.org/examples/en/index.html#chart-type-radar

  • @cyrilgorrieri
    @cyrilgorrieri 11 месяцев назад

    I would be curious to know which model you used.

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 11 месяцев назад

      Hi, I have put the model names in the description of the video

    • @cyrilgorrieri
      @cyrilgorrieri 10 месяцев назад

      @@DataScienceDemonstrated I don't see any models mentioned in the description. I would be expecting gpt-4, gpt-3.5-turbo or any other models OpenAI provide. It would also be great to add the prompt used to get the sentiment.

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 10 месяцев назад

      @@cyrilgorrieriIt’s gpt 3.5 turbo

  • @cyrilgorrieri
    @cyrilgorrieri 11 месяцев назад

    Which models did you use?

  • @kannadastocktrader3369
    @kannadastocktrader3369 11 месяцев назад

    Can u please upload part 2

  • @someronbakuli6878
    @someronbakuli6878 11 месяцев назад

    Nice explanation

  • @user-de5hs4gb6o
    @user-de5hs4gb6o 11 месяцев назад

    hi, thank you for the vivid explanation. may i ask a question: which software are you using to group different product items into clusters, and then visualize those clusters with color on the x,y coordinate?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated 11 месяцев назад

      Thanks! I have created my own platform , which is based on Python and JavaScript visualization libraries. You can access it here : experiencedatascience.com . You will be able to make similar clustering and visual as I have shown, without coding. Hope you enjoy it

  • @user-de5hs4gb6o
    @user-de5hs4gb6o 11 месяцев назад

    concisely lightening