Rezultati pretraživanja
  1. 29. sij

    This video explains 's amazing new Meena chatbot! An Evolved Transformer with 2.6B parameters on 341 GB / 40B words of conversation data to achieves remarkable chatbot performance! "Horses go to Hayvard!"

  2. Day 15. I'm studying machine learning concepts and algorithms. Later, I will work on their Python implementations. One day at at time. It's a lot! I have a long way to go but I'm happy with all I'm learning! 😊💯❤️

  3. prije 6 sati

    AI Weekly update for February 3rd, 2020! This update covers Google AI's Meena Chatbot, Microsoft's ImageBERT, blog posts on Curriculum Learning in RL and Contrastive Self-Supervised Learning, and more!

  4. Day - 19: Completed numpy module 😅 in Python for Data Science course and starring Pandas as next module

  5. Day 44 Today I continued with the Private AI Udacity course, I'm planning on finishing it by tomorrow.

  6. prije 5 sati

    Day 17: Read about the Decision Tree Algorithm. Turned out to be a simple and highly interpretable model.

    Prikaži ovu nit
  7. prije 7 sati

    Day 72: Finally, I got my certificate! Next step: rewrite course projects in python and publish it in GitHub+start reading Hands-on ML book by Aurélien géron

  8. prije 11 sati

    Since many features roughly follow normal distribution, I tried using the pdf to predict which of the four severity does the accident most likely belong. But results were terrible even on the training set(42% accuracy).

  9. Day 14. I started this course, Data Structures and Algorithms: I find it pretty useful and I'm glad I'm taking it!

  10. Plzz give me some guidance how can I move forward in career 🙏🙏..I know basics of coding have worked for 6 months,but have only 3 months of proof

    Prikaži ovu nit
  11. prije 13 sati

    R3 Days 15 to 70 of Finished: - "Neural Network and Deep Learning" - "Applied Machine Learning In Python" courses at

  12. prije 17 sati

    23/100 Not really a full day of "butt in seat" time, but I got some good problem solving in. Coding consisted of going back into some math and generalizing the hard numbers I used to originally get that part of the algorithm done.

    Prikaži ovu nit
  13. prije 22 sata

    Round 2 Day 42 of I am still going back and forth between perception and gradient descent. Looking for that 'click' moment to move on! Submitted the first ML algorithm and got the new one right after it :D

  14. 3. velj

    Day 39 : Working on my DeepLearning nanodegree from Udacity. Learned the black box theory of Gradient Deacent and used it to implement a neural network to predict bike sales.

  15. 2. velj

    Day 7: 1) Studied the problem of overfitting and it's solution by regularization. 2) Exploring Neural networks and started third week's assignment. 3) Parallelly enjoying image processing with openCV.

  16. 2. velj

    RT : RT : Day 26 of Took a deeper dive into Neural Networks, Gradient descent, Back…

  17. 2. velj

    Round 2 Day 41 of It was all about the GRADIENT DESCENT which is a famous optimization algorithm. I derived the formulas from scratch which helped me to see the importance of derivatives one more time.

  18. 2. velj

    Looking to meet people who are doing image analysis and computer vision

  19. 1. velj

    Day1: Starting sentdex series and picking up the first 3 videos .. Learned about loading the dataset,adding new coloumns and defining the features and the labels.

Čini se da učitavanje traje već neko vrijeme.

Twitter je možda preopterećen ili ima kratkotrajnih poteškoća u radu. Pokušajte ponovno ili potražite dodatne informacije u odjeljku Status Twittera.