machine-learning 321

  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. What is the difference between linear regression and logistic regression?
  21. Why does one hot encoding improve machine learning performance?
  22. Is there a rule-of-thumb for how to divide a dataset into training and validation sets?
  23. Machine Learning in Game AI
  24. Numpy 1-hot array
  25. machine learning libraries in C#
  26. How to interpret “loss” and “accuracy” for a machine learning model
  27. multi-layer perceptron (MLP) architecture: criteria for choosing number of hidden layers and size of the hidden layer?
  28. How to extract the decision rules from scikit-learn decision-tree?
  29. How can I build a model to distinguish tweets about Apple (Inc.) from tweets about apple (fruit)?
  30. Why must a nonlinear activation function be used in a backpropagation neural network?
  31. Is there a recommended package for machine learning in Python?
  32. What is an intuitive explanation of the Expectation Maximization technique?
  33. What is machine learning?
  34. TensorFlow, why was python the chosen language?
  35. How do I find Wally with Python?
  36. Estimating the number of neurons and number of layers of an artificial neural network
  37. Detecting patterns in waves
  38. How to compute precision, recall, accuracy and f1-score for the multiclass case with scikit learn?
  39. Why should weights of Neural Networks be initialized to random numbers?


  40. How to split data into 3 sets (train, validation and test)?
  41. Python: tf-idf-cosine: to find document similarity
  42. How to build random forests in R with missing (NA) values?
  43. why gradient descent when we can solve linear regression analytically
  44. How to interpret Poolallocator messages in tensorflow?
  45. Anyone Recommend a Good Tutorial on Conditional Random Fields
  46. Machine learning in OCaml or Haskell?
  47. Open Source Neural Network Library
  48. Unsupervised clustering with unknown number of clusters
  49. How to get most informative features for scikit-learn classifiers?
  50. Training a Neural Network with Reinforcement learning