machine-learning 355

  1. Role of Bias in Neural Networks
  2. A simple explanation of Naive Bayes Classification
  3. What is the difference between a Generative and Discriminative Algorithm?
  4. How does the Google “Did you mean?” Algorithm work?
  5. Tensorflow: how to save/restore a model?
  6. What are advantages of Artificial Neural Networks over Support Vector Machines?
  7. What is the difference between supervised learning and unsupervised learning?
  8. What's the difference between softmax and softmax_cross_entropy_with_logits?
  9. tensorflow not found in pip
  10. Which machine learning classifier to choose, in general?
  11. Difference between classification and clustering in data mining?
  12. How to implement the Softmax function in Python
  13. How to understand Locality Sensitive Hashing?
  14. How does Apple find dates, times and addresses in emails?
  15. Nearest neighbors in high-dimensional data?
  16. Is it possible to specify your own distance function using scikit-learn K-Means Clustering?
  17. How to train an artificial neural network to play Diablo 2 using visual input?
  18. Save classifier to disk in scikit-learn
  19. When to use Genetic Algorithms vs. when to use Neural Networks?
  20. Why does one hot encoding improve machine learning performance?
  21. Machine Learning in Game AI
  22. machine learning libraries in C#
  23. Is there a rule-of-thumb for how to divide a dataset into training and validation sets?
  24. multi-layer perceptron (MLP) architecture: criteria for choosing number of hidden layers and size of the hidden layer?
  25. How can I build a model to distinguish tweets about Apple (Inc.) from tweets about apple (fruit)?
  26. What is the difference between linear regression and logistic regression?
  27. Is there a recommended package for machine learning in Python?
  28. How do I find Wally with Python?
  29. What is machine learning?
  30. Detecting patterns in waves
  31. Estimating the number of neurons and number of layers of an artificial neural network
  32. how to extract the decision rules from scikit-learn decision-tree?
  33. What is an intuitive explanation of the Expectation Maximization technique?
  34. Numpy 1-hot array
  35. How to interpret “loss” and “accuracy” for a machine learning model
  36. How to compute precision, recall, accuracy and f1-score for the multiclass case with scikit learn?
  37. Why must a nonlinear activation function be used in a backpropagation neural network?
  38. Anyone Recommend a Good Tutorial on Conditional Random Fields
  39. Machine learning in OCaml or Haskell?
  40. How to build random forests in R with missing (NA) values?
  41. How to interpret Poolallocator messages in tensorflow?
  42. Logo recognition in images
  43. Training a Neural Network with Reinforcement learning
  44. Python: tf-idf-cosine: to find document similarity
  45. How to get most informative features for scikit-learn classifiers?
  46. TensorFlow, why was python the chosen language?
  47. Perceptron learning algorithm not converging to 0
  48. Ways to improve the accuracy of a Naive Bayes Classifier?
  49. Resources for working with Machine Learning in F#
  50. Unsupervised clustering with unknown number of clusters