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Data Science at Home

By Francesco Gadaleta

Technology, AI, machine learning and algorithms. Come join the discussion on Discord! https://discord.gg/4UNKGf3

  1. 1.
    Distill data and train faster, better, cheaper (Ep. 128)11/17/2020
    23:46
  2. 2.
    Machine Learning in Rust: Amadeus with Alec Mocatta [RB] (ep. 127)11/11/2020
    24:19
  3. 3.
    Top-3 ways to put machine learning models into production (Ep. 126)11/07/2020
    20:27
  4. 4.
    Remove noise from data with deep learning (Ep.125)11/03/2020
    23:59
  5. 5.
    What is contrastive learning and why it is so powerful? (Ep. 124)10/30/2020
    26:12
  6. 6.
    Neural search (Ep. 123)10/23/2020
    19:18
  7. 7.
    Let's talk about federated learning (Ep. 122)10/18/2020
    30:10
  8. 8.
    How to test machine learning in production (Ep. 121)10/11/2020
    28:48
  1. 9.
    Why synthetic data cannot boost machine learning (Ep. 120)09/26/2020
    23:23
  2. 10.
    Machine learning in production: best practices [LIVE from twitch.tv] (Ep. 119)09/16/2020
    37:31
  3. 11.
    Testing in machine learning: checking deeplearning models (Ep. 118)09/04/2020
    18:17
  4. 12.
    Testing in machine learning: generating tests and data (Ep. 117)08/29/2020
    20:18
  5. 13.
    Why you care about homomorphic encryption (Ep. 116)08/12/2020
    18:50
  6. 14.
    Test-First machine learning (Ep. 115)08/03/2020
    19:43
  7. 15.
    GPT-3 cannot code (and never will) (Ep. 114)07/26/2020
    19:06
  8. 16.
    Make Stochastic Gradient Descent Fast Again (Ep. 113)07/22/2020
    20:35
  9. 17.
    What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)07/19/2020
    21:10
  10. 18.
    [RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)07/03/2020
    36:54
  11. 19.
    Rust and machine learning #4: practical tools (Ep. 110)06/29/2020
    24:18
  12. 20.
    Rust and machine learning #3 with Alec Mocatta (Ep. 109)06/22/2020
    23:58
  13. 21.
    Rust and machine learning #2 with Luca Palmieri (Ep. 108)06/19/2020
    27:02
  14. 22.
    Rust and machine learning #1 (Ep. 107)06/17/2020
    22:27
  15. 23.
    Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)(Ep. 106)06/15/2020
    16:20
  16. 24.
    Compressing deep learning models: rewinding (Ep.105)06/01/2020
    15:31
  17. 25.
    Compressing deep learning models: distillation (Ep.104)05/20/2020
    22:19
  18. 26.
    Pandemics and the risks of collecting data (Ep. 103)05/08/2020
    20:09
  19. 27.
    Why average can get your predictions very wrong (ep. 102)04/19/2020
    14:47
  20. 28.
    Activate deep learning neurons faster with Dynamic RELU (ep. 101)04/01/2020
    22:18
  21. 29.
    WARNING!! Neural networks can memorize secrets (ep. 100)03/23/2020
    24:16
  22. 30.
    Attacks to machine learning model: inferring ownership of training data (Ep. 99) 03/14/2020
    19:39
  23. 31.
    Don't be naive with data anonymization (Ep. 98)03/08/2020
    13:41
  24. 32.
    Why sharing real data is dangerous (Ep. 97)03/01/2020
    10:35
  25. 33.
    Building reproducible machine learning in production (Ep. 96)02/22/2020
    14:20
  26. 34.
    Bridging the gap between data science and data engineering: metrics (Ep. 95)02/14/2020
    13:25
  27. 35.
    A big welcome to Pryml: faster machine learning applications to production (Ep. 94)02/07/2020
    9:26
  28. 36.
    It's cold outside. Let's speak about AI winter (Ep. 93)12/31/2019
    36:48
  29. 37.
    The dark side of AI: bias in the machine (Ep. 92)12/28/2019
    20:26
  30. 38.
    The dark side of AI: metadata and the death of privacy (Ep. 91)12/23/2019
    23:00
  31. 39.
    The dark side of AI: recommend and manipulate (Ep. 90)12/11/2019
    20:33
  32. 40.
    The dark side of AI: social media and the optimization of addiction (Ep. 89)12/03/2019
    22:45
  33. 41.
    More powerful deep learning with transformers (Ep. 84) (Rebroadcast)11/27/2019
    37:44
  34. 42.
    How to improve the stability of training a GAN (Ep. 88)11/18/2019
    28:20
  35. 43.
    What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)11/12/2019
    19:37
  36. 44.
    Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)11/05/2019
    44:53
  37. 45.
    [RB] How to generate very large images with GANs (Ep. 85)11/04/2019
    14:41
  38. 46.
    More powerful deep learning with transformers (Ep. 84)10/27/2019
    37:44
  39. 47.
    [RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)10/18/2019
    37:47
  40. 48.
    What is wrong with reinforcement learning? (Ep. 82)10/15/2019
    21:48
  41. 49.
    Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history (Ep. 81)10/10/2019
    32:21
  42. 50.
    Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)10/01/2019
    34:04
  43. 51.
    [RB] How to scale AI in your organisation (Ep. 79)09/26/2019
    13:21
  44. 52.
    Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 78)09/23/2019
    37:47
  45. 53.
    Training neural networks faster without GPU [RB] (Ep. 77)09/17/2019
    22:21
  46. 54.
    How to generate very large images with GANs (Ep. 76)09/06/2019
    14:41
  47. 55.
    [RB] Complex video analysis made easy with Videoflow (Ep. 75)08/29/2019
    30:42
  48. 56.
    [RB] Validate neural networks without data with Dr. Charles Martin (Ep. 74)08/27/2019
    44:46
  49. 57.
    How to cluster tabular data with Markov Clustering (Ep. 73)08/20/2019
    20:43
  50. 58.
    Waterfall or Agile? The best methodology for AI and machine learning (Ep. 72)08/14/2019
    14:26
  51. 59.
    Training neural networks faster without GPU (Ep. 71)08/06/2019
    22:21
  52. 60.
    Validate neural networks without data with Dr. Charles Martin (Ep. 70)07/23/2019
    44:46
  53. 61.
    Complex video analysis made easy with Videoflow (Ep. 69)07/16/2019
    30:42
  54. 62.
    Episode 68: AI and the future of banking with Chris Skinner [RB]07/09/2019
    41:42
  55. 63.
    Episode 67: Classic Computer Science Problems in Python07/02/2019
    28:35
  56. 64.
    Episode 66: More intelligent machines with self-supervised learning06/25/2019
    18:56
  57. 65.
    Episode 65: AI knows biology. Or does it?06/23/2019
    12:14
  58. 66.
    Episode 64: Get the best shot at NLP sentiment analysis06/14/2019
    12:58
  59. 67.
    Episode 63: Financial time series and machine learning 06/04/2019
    21:08
  60. 68.
    Episode 62: AI and the future of banking with Chris Skinner05/28/2019
    42:03
  61. 69.
    Episode 61: The 4 best use cases of entropy in machine learning05/21/2019
    21:35
  62. 70.
    Episode 60: Predicting your mouse click (and a crash course in deeplearning)05/16/2019
    39:50
  63. 71.
    Episode 59: How to fool a smart camera with deep learning05/07/2019
    24:11
  64. 72.
    Episode 58: There is physics in deep learning!04/30/2019
    19:55
  65. 73.
    Episode 57: Neural networks with infinite layers04/23/2019
    16:19
  66. 74.
    Episode 56: The graph network 04/16/2019
    16:34
  67. 75.
    Episode 55: Beyond deep learning 04/09/2019
    17:23
  68. 76.
    Episode 54: Reproducible machine learning03/09/2019
    11:50
  69. 77.
    Episode 53: Estimating uncertainty with neural networks01/23/2019
    15:08
  70. 78.
    Episode 52: why do machine learning models fail? [RB]01/17/2019
    15:58
  71. 79.
    Episode 51: Decentralized machine learning in the data marketplace (part 2)01/08/2019
    23:08
  72. 80.
    Episode 50: Decentralized machine learning in the data marketplace 12/26/2018
    24:17
  73. 81.
    Episode 49: The promises of Artificial Intelligence12/19/2018
    21:00
  74. 82.
    Episode 48: Coffee, Machine Learning and Blockchain10/21/2018
    28:48
  75. 83.
    Episode 47: Are you ready for AI winter? [Rebroadcast]09/11/2018
    56:55
  76. 84.
    Episode 46: why do machine learning models fail? (Part 2)09/04/2018
    17:12
  77. 85.
    Episode 45: why do machine learning models fail?08/28/2018
    16:21
  78. 86.
    Episode 44: The predictive power of metadata08/21/2018
    21:08
  79. 87.
    Episode 43: Applied Text Analysis with Python (interview with Rebecca Bilbro)08/14/2018
    36:32
  80. 88.
    Episode 42: Attacking deep learning models (rebroadcast)08/07/2018
    29:04
  81. 89.
    Episode 41: How can deep neural networks reason07/31/2018
    18:04
  82. 90.
    Episode 40: Deep learning and image compression07/24/2018
    17:20
  83. 91.
    Episode 39: What is L1-norm and L2-norm?07/19/2018
    21:55
  84. 92.
    Episode 38: Collective intelligence (Part 2)07/17/2018
    46:36
  85. 93.
    Episode 38: Collective intelligence (Part 1)07/12/2018
    30:58
  86. 94.
    Episode 37: Predicting the weather with deep learning07/09/2018
    26:25
  87. 95.
    Episode 36: The dangers of machine learning and medicine07/03/2018
    22:07
  88. 96.
    Episode 35: Attacking deep learning models06/29/2018
    29:13
  89. 97.
    Episode 34: Get ready for AI winter06/22/2018
    59:04
  90. 98.
    Episode 33: Decentralized Machine Learning and the proof-of-train06/11/2018
    17:40
  91. 99.
    Episode 32: I am back. I have been building fitchain06/04/2018
    23:14
  92. 100.
    Founder Interview – Francesco Gadaleta of Fitchain05/24/2018
    31:04

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