diff --git a/course-zoomcamp/02-regression/01-car-price-intro.md b/course-zoomcamp/02-regression/01-car-price-intro.md index 31bf75a88..d5109dea1 100644 --- a/course-zoomcamp/02-regression/01-car-price-intro.md +++ b/course-zoomcamp/02-regression/01-car-price-intro.md @@ -34,7 +34,7 @@ The code and dataset are available at this [link](https://github.com/alexeygrigo -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/02-data-preparation.md b/course-zoomcamp/02-regression/02-data-preparation.md index 564d0a205..4d4f8b5a2 100644 --- a/course-zoomcamp/02-regression/02-data-preparation.md +++ b/course-zoomcamp/02-regression/02-data-preparation.md @@ -16,7 +16,7 @@ * df.columns.str.lower() - lowercase all the letters * df.columns.str.replace(' ', '_') - replace the space separator * df.dtypes - retrieve data types of all features -* df.index - retrive indices of a dataframe +* df.index - retrieve indices of a dataframe The entire code of this project is available in [this jupyter notebook](https://github.com/alexeygrigorev/mlbookcamp-code/blob/master/chapter-02-car-price/02-carprice.ipynb). @@ -30,7 +30,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/03-eda.md b/course-zoomcamp/02-regression/03-eda.md index d843cecc1..ae6a56f73 100644 --- a/course-zoomcamp/02-regression/03-eda.md +++ b/course-zoomcamp/02-regression/03-eda.md @@ -36,7 +36,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/04-validation-framework.md b/course-zoomcamp/02-regression/04-validation-framework.md index 0569cd38a..792a50cdb 100644 --- a/course-zoomcamp/02-regression/04-validation-framework.md +++ b/course-zoomcamp/02-regression/04-validation-framework.md @@ -13,7 +13,7 @@ In general, the dataset is split into three parts: training, validation, and tes **Pandas attributes and methods:** * `df.iloc[]` - returns subsets of records of a dataframe, being selected by numerical indices -* `df.rest_index()` - restate the orginal indices +* `df.reset_index()` - restate the orginal indices * `del df[col]` - eliminates target variable **Numpy methods:** @@ -34,7 +34,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/05-linear-regression-simple.md b/course-zoomcamp/02-regression/05-linear-regression-simple.md index b57dc47b8..fe56518ce 100644 --- a/course-zoomcamp/02-regression/05-linear-regression-simple.md +++ b/course-zoomcamp/02-regression/05-linear-regression-simple.md @@ -11,7 +11,7 @@ Model for solving regression tasks, in which the objective is to adjust a line for the data and make predictions on new values. The input of this model is the feature matrix and a y vector of predictions is obtained, trying to be as close as possible to the actual y values. The LR formula is the sum of the bias term (WO), which refers to the predictions if there is no information, and each of the feature values times their corresponding weights. We need to -assure that the result is showed on the untransformed scale. +assure that the result is shown on the untransformed scale. The entire code of this project is available in [this jupyter notebook](https://github.com/alexeygrigorev/mlbookcamp-code/blob/master/chapter-02-car-price/02-carprice.ipynb). @@ -25,7 +25,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/06-linear-regression-vector.md b/course-zoomcamp/02-regression/06-linear-regression-vector.md index 0fb1f3137..66994bdab 100644 --- a/course-zoomcamp/02-regression/06-linear-regression-vector.md +++ b/course-zoomcamp/02-regression/06-linear-regression-vector.md @@ -24,7 +24,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/07-linear-regression-training.md b/course-zoomcamp/02-regression/07-linear-regression-training.md index f1264d849..a738e829e 100644 --- a/course-zoomcamp/02-regression/07-linear-regression-training.md +++ b/course-zoomcamp/02-regression/07-linear-regression-training.md @@ -27,7 +27,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/08-baseline-model.md b/course-zoomcamp/02-regression/08-baseline-model.md index 89ee23a40..0e0678869 100644 --- a/course-zoomcamp/02-regression/08-baseline-model.md +++ b/course-zoomcamp/02-regression/08-baseline-model.md @@ -24,7 +24,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/09-rmse.md b/course-zoomcamp/02-regression/09-rmse.md index 742221ae6..a4fa141c6 100644 --- a/course-zoomcamp/02-regression/09-rmse.md +++ b/course-zoomcamp/02-regression/09-rmse.md @@ -22,7 +22,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/10-car-price-validation.md b/course-zoomcamp/02-regression/10-car-price-validation.md index a1414f4ad..b58acd7ac 100644 --- a/course-zoomcamp/02-regression/10-car-price-validation.md +++ b/course-zoomcamp/02-regression/10-car-price-validation.md @@ -23,7 +23,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/11-feature-engineering.md b/course-zoomcamp/02-regression/11-feature-engineering.md index d283cc5f5..8703612b4 100644 --- a/course-zoomcamp/02-regression/11-feature-engineering.md +++ b/course-zoomcamp/02-regression/11-feature-engineering.md @@ -24,7 +24,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/12-categorical-variables.md b/course-zoomcamp/02-regression/12-categorical-variables.md index a3644a0bb..b738670a1 100644 --- a/course-zoomcamp/02-regression/12-categorical-variables.md +++ b/course-zoomcamp/02-regression/12-categorical-variables.md @@ -30,7 +30,7 @@ This way of encoding categorical features is called "one-hot encoding". We'll learn more about it in Session 3. -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/13-regularization.md b/course-zoomcamp/02-regression/13-regularization.md index 6b556a27b..cf55d3464 100644 --- a/course-zoomcamp/02-regression/13-regularization.md +++ b/course-zoomcamp/02-regression/13-regularization.md @@ -35,13 +35,13 @@ The entire code of this project is available in [this jupyter notebook](https:// I mentioned the term *linear combination* in the video, but didn't explain what it means. So if you're interested what it means, you can read here -* One column is a of others when you can express one column of a matrix as a sum of others columns +* One column is a linear combination of others when you can express one column of a matrix as a sum of others columns * The simplest example is when a column is an exact duplicate of another column * Another example. Let's say we have 3 columns: `a`, `b`, `c`. If `c = 0.2 * a + 0.5 * b`, then `c` is a linear combination of `a` and `b` * More formal definition: https://en.wikipedia.org/wiki/Linear_combination -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/14-tuning-model.md b/course-zoomcamp/02-regression/14-tuning-model.md index 65e7b9723..c79ef0aae 100644 --- a/course-zoomcamp/02-regression/14-tuning-model.md +++ b/course-zoomcamp/02-regression/14-tuning-model.md @@ -23,7 +23,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/15-using-model.md b/course-zoomcamp/02-regression/15-using-model.md index 6c154effb..f306b1481 100644 --- a/course-zoomcamp/02-regression/15-using-model.md +++ b/course-zoomcamp/02-regression/15-using-model.md @@ -8,7 +8,7 @@ ## Notes After finding the best model and its parameters, it was trained with training and validation partitions and the final evaluation was calculated on the test partition. -Finally, the final model was used t predict the price of new cars. +Finally, the final model was used to predict the price of new cars. The entire code of this project is available in [this jupyter notebook](https://github.com/alexeygrigorev/mlbookcamp-code/blob/master/chapter-02-car-price/02-carprice.ipynb). @@ -22,7 +22,7 @@ The entire code of this project is available in [this jupyter notebook](https:// -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/16-summary.md b/course-zoomcamp/02-regression/16-summary.md index 91a858636..7ce7012a2 100644 --- a/course-zoomcamp/02-regression/16-summary.md +++ b/course-zoomcamp/02-regression/16-summary.md @@ -21,7 +21,7 @@ were explained using the problem to predict the price of cars. -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./) diff --git a/course-zoomcamp/02-regression/17-explore-more.md b/course-zoomcamp/02-regression/17-explore-more.md index 1bef5bbf5..bbe1e9a02 100644 --- a/course-zoomcamp/02-regression/17-explore-more.md +++ b/course-zoomcamp/02-regression/17-explore-more.md @@ -3,7 +3,7 @@ ### Questions -* In this project, we We included only 5 top features. What happens if we include 10? +* In this project, we included only 5 top features. What happens if we include 10? > That's not a graded homework, it's just for you if you want to try more things on this project @@ -17,7 +17,7 @@ Here are other datasets that you can play with to learn more about the topic: * UCI ML Repository contains a lot of other datasets suitable for practicing regression - https://archive.ics.uci.edu/ml/datasets.php?task=reg -## Nagivation +## Navigation * [Machine Learning Zoomcamp course](../) * [Session 2: Machine Learning for Regression](./)