diff --git a/src/TensorFlowNET.Core/NumPy/Implementation/RandomizedImpl.cs b/src/TensorFlowNET.Core/NumPy/Implementation/RandomizedImpl.cs
index c72bd2de..9d594637 100644
--- a/src/TensorFlowNET.Core/NumPy/Implementation/RandomizedImpl.cs
+++ b/src/TensorFlowNET.Core/NumPy/Implementation/RandomizedImpl.cs
@@ -36,6 +36,11 @@ namespace Tensorflow.NumPy
             return new NDArray(tensor);
         }
 
+        [AutoNumPy]
+        public NDArray randn(params int[] shape)
+            => new NDArray(random_ops.random_normal(shape ?? Shape.Scalar));
+
+        [AutoNumPy]
         public NDArray normal(float loc = 0.0f, float scale = 1.0f, Shape size = null)
             => new NDArray(random_ops.random_normal(size ?? Shape.Scalar, mean: loc, stddev: scale));
     }
diff --git a/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs b/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
index 88dca940..53401a44 100644
--- a/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
+++ b/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
@@ -21,7 +21,7 @@ namespace Tensorflow.NumPy
             => nd.dtype == TF_DataType.TF_BOOL ? *(bool*)nd.data : NDArrayConverter.Scalar<bool>(nd);
 
         public unsafe static implicit operator byte(NDArray nd)
-            => nd.dtype == TF_DataType.TF_INT8 ? *(byte*)nd.data : NDArrayConverter.Scalar<byte>(nd);
+            => nd.dtype == TF_DataType.TF_UINT8 ? *(byte*)nd.data : NDArrayConverter.Scalar<byte>(nd);
 
         public unsafe static implicit operator int(NDArray nd)
             => nd.dtype == TF_DataType.TF_INT32 ? *(int*)nd.data : NDArrayConverter.Scalar<int>(nd);
diff --git a/src/TensorFlowNET.Core/NumPy/NDArrayConverter.cs b/src/TensorFlowNET.Core/NumPy/NDArrayConverter.cs
index 921c213c..fbab95a9 100644
--- a/src/TensorFlowNET.Core/NumPy/NDArrayConverter.cs
+++ b/src/TensorFlowNET.Core/NumPy/NDArrayConverter.cs
@@ -10,14 +10,25 @@ namespace Tensorflow.NumPy
         public unsafe static T Scalar<T>(NDArray nd) where T : unmanaged
             => nd.dtype switch
             {
+                TF_DataType.TF_UINT8 => Scalar<T>(*(byte*)nd.data),
                 TF_DataType.TF_FLOAT => Scalar<T>(*(float*)nd.data),
                 TF_DataType.TF_INT64 => Scalar<T>(*(long*)nd.data),
                 _ => throw new NotImplementedException("")
             };
 
+        static T Scalar<T>(byte input)
+            => Type.GetTypeCode(typeof(T)) switch
+            {
+                TypeCode.Byte => (T)Convert.ChangeType(input, TypeCode.Byte),
+                TypeCode.Int32 => (T)Convert.ChangeType(input, TypeCode.Int32),
+                TypeCode.Single => (T)Convert.ChangeType(input, TypeCode.Single),
+                _ => throw new NotImplementedException("")
+            };
+
         static T Scalar<T>(float input)
             => Type.GetTypeCode(typeof(T)) switch
             {
+                TypeCode.Byte => (T)Convert.ChangeType(input, TypeCode.Byte),
                 TypeCode.Int32 => (T)Convert.ChangeType(input, TypeCode.Int32),
                 TypeCode.Single => (T)Convert.ChangeType(input, TypeCode.Single),
                 _ => throw new NotImplementedException("")
@@ -26,6 +37,7 @@ namespace Tensorflow.NumPy
         static T Scalar<T>(long input)
             => Type.GetTypeCode(typeof(T)) switch
             {
+                TypeCode.Byte => (T)Convert.ChangeType(input, TypeCode.Byte),
                 TypeCode.Int32 => (T)Convert.ChangeType(input, TypeCode.Int32),
                 TypeCode.Single => (T)Convert.ChangeType(input, TypeCode.Single),
                 _ => throw new NotImplementedException("")
diff --git a/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs b/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs
index 39d02dcd..440a6faa 100644
--- a/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs
+++ b/src/TensorFlowNET.Core/NumPy/Numpy.Math.cs
@@ -9,6 +9,9 @@ namespace Tensorflow.NumPy
 {
     public partial class np
     {
+        [AutoNumPy]
+        public static NDArray cos(NDArray x) => new NDArray(math_ops.cos(x));
+
         [AutoNumPy]
         public static NDArray exp(NDArray x) => new NDArray(tf.exp(x));
 
@@ -38,6 +41,12 @@ namespace Tensorflow.NumPy
         public static NDArray prod<T>(params T[] array) where T : unmanaged
             => new NDArray(tf.reduce_prod(new NDArray(array)));
 
+        [AutoNumPy]
+        public static NDArray power(NDArray x, NDArray y) => new NDArray(tf.pow(x, y));
+
+        [AutoNumPy]
+        public static NDArray sin(NDArray x) => new NDArray(math_ops.sin(x));
+
         [AutoNumPy]
         public static NDArray sqrt(NDArray x) => new NDArray(tf.sqrt(x));
 
diff --git a/src/TensorFlowNET.Core/Operations/math_ops.cs b/src/TensorFlowNET.Core/Operations/math_ops.cs
index 71992f35..97b9d13f 100644
--- a/src/TensorFlowNET.Core/Operations/math_ops.cs
+++ b/src/TensorFlowNET.Core/Operations/math_ops.cs
@@ -134,6 +134,9 @@ namespace Tensorflow
             });
         }
 
+        public static Tensor cos(Tensor x, string name = null)
+            => tf.Context.ExecuteOp("Cos", name, new ExecuteOpArgs(x));
+
         public static Tensor saturate_cast(Tensor value, TF_DataType dtype, string name = null)
         {
             return tf_with(ops.name_scope(name, "saturate_cast", new[] { value }), name =>
@@ -373,6 +376,9 @@ namespace Tensorflow
         public static Tensor sign<T>(T x, string name = null)
             => gen_math_ops.sign(x, name: name);
 
+        public static Tensor sin(Tensor x, string name = null)
+            => tf.Context.ExecuteOp("Sin", name, new ExecuteOpArgs(x));
+
         /// <summary>
         /// Returns (x - y)(x - y) element-wise.
         /// </summary>
diff --git a/test/TensorFlowNET.UnitTest/NumPy/Randomize.Test.cs b/test/TensorFlowNET.UnitTest/NumPy/Randomize.Test.cs
index 5916324f..55801f55 100644
--- a/test/TensorFlowNET.UnitTest/NumPy/Randomize.Test.cs
+++ b/test/TensorFlowNET.UnitTest/NumPy/Randomize.Test.cs
@@ -33,5 +33,15 @@ namespace TensorFlowNET.UnitTest.NumPy
             var x = np.random.normal(0, 0.1f, 1000);
             Equal(np.mean(x), 0f);
         }
+
+        [TestMethod]
+        public void randn()
+        {
+            var x = np.random.randn();
+            Assert.AreEqual(np.float32, x.dtype);
+
+            x = np.random.randn(2, 4);
+            Equal(np.mean(x), 0f);
+        }
     }
 }
diff --git a/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs b/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs
index 072f0079..a0e6fa4e 100644
--- a/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs
+++ b/test/TensorFlowNET.UnitTest/Numpy/Math.Test.cs
@@ -43,5 +43,27 @@ namespace TensorFlowNET.UnitTest.NumPy
             var y = x / 2;
             Assert.AreEqual(y.dtype, np.float32);
         }
+
+        [TestMethod]
+        public void sin()
+        {
+            var x = np.sin(np.pi / 2);
+            Assert.AreEqual(x, 1d);
+        }
+
+        [TestMethod]
+        public void cos()
+        {
+            var x = np.cos(np.pi / 2);
+            Assert.AreEqual(x, 6.123233995736766e-17);
+        }
+
+        [TestMethod]
+        public void power()
+        {
+            var x = np.arange(6);
+            var y = np.power(x, 3);
+            Assert.AreEqual(y, new[] { 0, 1, 8, 27, 64, 125 });
+        }
     }
 }
diff --git a/test/TensorFlowNET.UnitTest/Tensorflow.Binding.UnitTest.csproj b/test/TensorFlowNET.UnitTest/Tensorflow.Binding.UnitTest.csproj
index 2aef756a..4c989e05 100644
--- a/test/TensorFlowNET.UnitTest/Tensorflow.Binding.UnitTest.csproj
+++ b/test/TensorFlowNET.UnitTest/Tensorflow.Binding.UnitTest.csproj
@@ -55,7 +55,7 @@
   </ItemGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\..\src\TensorFlowNET.Recommenders\Tensorflow.Recommenders.csproj" />
+    <ProjectReference Include="..\..\src\TensorFlowNET.Core\Tensorflow.Binding.csproj" />
     <ProjectReference Include="..\..\src\TensorFlowNET.Text\Tensorflow.Text.csproj" />
   </ItemGroup>