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Journals (15)
- Jun 8, 2026
Reinforcement Learning(RL) trains an agent to take actions in an environment, the agent does not get told what to action correct, it basically gets a reward signal instead.
- Jun 3, 2026
Principal component analysis(PCA) allows us to take data with a lot of features say hundreds or thousands of features and reduce it to very small number of features say two or five features.
- Jun 2, 2026
Recommender system predicts how a user would rank or respond to items they haven't seen yet, then surface with the highest predicted score
- Jun 1, 2026
Anomaly detection looks at unlabeled dataset of normal examples, learns what normal looks like, then flags new examples that looks different
- May 26, 2026
Clustering looks at a dataset and tries to find points that are similar to each other and group them together
- May 25, 2026
Learned about the Gini index as a measure of impurity for decision trees
- May 22, 2026
Learned a whole bunch about decision trees.
- May 21, 2026
Learned about model diagnosis, when a model performs poorly, we can do the following: - Collect more training data - Try a smaller set of features - Add more features - Add polynomial features - Decrease the regularization parameter $\lambda$ - Increase $\lambda$ - Make the model bigger - Train longer
- May 20, 2026
Learned about the steps involved in training a neural network which are: specify the model, specify the loss and cost function and then train the model on the training dataset to minimize the cost function.
- May 19, 2026
Neuron is a computational unit which takes a vector of input, computes a weighted sum plus a bias, then apply a non-linear activation function to produce a single output.
- May 15, 2026
Learned classification with logistic regression
- May 14, 2026
Learned about regression with multiple input variables
- May 13, 2026
No ML today
- May 12, 2026
Not much
- May 11, 2026
Explored intro to machine learning and types of machine learning models