diff --git a/src/dl_workshop/answers.py b/src/dl_workshop/answers.py
index 378f518..20edd5f 100644
--- a/src/dl_workshop/answers.py
+++ b/src/dl_workshop/answers.py
@@ -81,7 +81,7 @@ def logistic_loss(params, model, x, y):
 
 
 def f(w):
-    return w ** 2 + 3 * w - 5
+    return w**2 + 3 * w - 5
 
 
 def df(w):
diff --git a/src/dl_workshop/gaussian_mixture.py b/src/dl_workshop/gaussian_mixture.py
index 9aa6cb2..8e7dd73 100644
--- a/src/dl_workshop/gaussian_mixture.py
+++ b/src/dl_workshop/gaussian_mixture.py
@@ -251,7 +251,6 @@ def joint_loglike(
     log_component_scales,
     observed_data,
 ):
-
     # logpdf of weights under concentrations prior
     logp_weights = component_probs_loglike(
         log_component_weights, log_concentration
diff --git a/src/dl_workshop/jax_idioms.py b/src/dl_workshop/jax_idioms.py
index e3b141e..4910bf1 100644
--- a/src/dl_workshop/jax_idioms.py
+++ b/src/dl_workshop/jax_idioms.py
@@ -93,7 +93,7 @@ def randomness_ex_3(key, num_realizations: int, grw_draw: Callable):
 
 def goldfield(x, y):
     """All credit to https://www.analyzemath.com/calculus/multivariable/maxima_minima.html for this function."""
-    return (2 * x ** 2) - (4 * x * y) + (y ** 4 + 2)
+    return (2 * x**2) - (4 * x * y) + (y**4 + 2)
 
 
 def grad_ex_1():