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Fix errors reported during Japanese translation

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stefanv committed Oct 23, 2018
1 parent df81fd9 commit ec314b25d5c3cb7edb1b26450744bb3123712274
Showing with 4 additions and 5 deletions.
  1. +3 −2 markdown/ch1.markdown
  2. +1 −1 markdown/ch5.markdown
  3. +0 −2 markdown/ch8.markdown
@@ -513,10 +513,11 @@ import matplotlib.pyplot as plt
plt.style.use('style/elegant.mplstyle')
```


> **A Quick Note on Plotting {.callout}**
>
> The preceding code does a few neat things to make our plots prettier.
>
> First, `%matplotlib inline` is a Jupyter notebook [magic
> command](http://ipython.org/ipython-doc/dev/interactive/tutorial.html#magics-explained),
> that simply makes all plots appear in the notebook rather than pop up a new
@@ -600,7 +601,7 @@ def reduce_xaxis_labels(ax, factor):
```

```python
# Bar plot of expression counts by individual
# Box plot of expression counts by individual
fig, ax = plt.subplots(figsize=(4.8, 2.4))
with plt.style.context('style/thinner.mplstyle'):
@@ -114,7 +114,7 @@ If we want to measure how well we are doing, we have to count the above kinds of
(This is also sometimes called a confusion matrix. The name is apt.)
For this, we place the prediction labels along the rows and the ground truth labels along the columns.
Then we count the number of times they correspond.
So, for example, since there are 4 true positives (where `pred` and `gt` are both 1), the matrix will have a value of 3 at position (1, 1).
So, for example, since there are 4 true positives (where `pred` and `gt` are both 1), the matrix will have a value of 4 at position (1, 1).

Generally:

@@ -85,8 +85,6 @@ Let's check that we get the same result with both methods:
```python
# We set the random seed so we will get consistent results
np.random.seed(seed=7)
# Set print options to show only 3 significant digits
np.set_printoptions(precision=3, suppress=True)
arr = np.random.rand(1000) + 0.5
result_batch = sum(log_all_standard(arr))

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