# Math equation is broken

See original GitHub issue```
### Linear Models and Least Squares
Given a vector of inputs $X^T=(X_1, X_2, \ldots, X_p)$, we predict output $Y$ via the model
$$
\hat{Y} = \hat{\beta}_0 + \sum_{j=1}^p X_j \hat{\beta}_j
$$
The term $\hat{\beta}_0$ is the intercept, also known as the *bias* in machine learning. Often it is convenient to include the constant variable 1 in $X$, include $\hat{\beta_0}$ in the vector of coefficients $\hat{\beta}$, and then write the linear model in vector form as an inner product
$$
\hat{Y} = X^T \hat{\beta}
$$
where $X^T$ denotes vector or matrix transpose ($X$ being a column vector). Here we are modeling a single output, so $\hat{Y}$ is a scalar; in general $\hat{Y}$ can be a $K$-vector, in which case $\beta$ would be a $p \times K$ matrix of coefficients. In the $(p+1)$-dimensional input-output space, $(X, \hat{Y})$ represents a hyperplane. If the constant is included in $X$, then the hyperplane includes the origin and is a subspace; if not; it is an affine set cutting the $Y$-axis at the point $(0, \hat{\beta}_0)$. From now on we assume that the intercept is included in $\hat{\beta}$.
```

In typora:

```
with open('temp.md', "r", encoding="utf-8") as mdFile:
newPage = page.children.add_new(PageBlock, title=mdFile.name)
txt = mdFile.read()
txt_list = re.split(pattern, txt)
for i, string in enumerate(txt_list):
if string == '':
txt_list[i] = '\n'
new_txt = ''.join(txt_list)
rendered = convert(new_txt,addLatexExtension(NotionPyRenderer))
for blockDescriptor in rendered:
uploadBlock(blockDescriptor, newPage, mdFile.name)
```

The equation is broken

### Issue Analytics

- State:
- Created 3 years ago
- Comments:10 (6 by maintainers)

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## Top GitHub Comments

@Cobertos Thanks. I get it works.

Upstream tag for the inline equation issue. Open to ideas to fix the newline thing, can’t think of an easy way to integrate that