diff --git a/mandelbrot_numba_fixed.ipynb b/mandelbrot_numba_fixed.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# A Numba Mandelbrot Example (Fixed for Modern Python/Numba)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from numba import cuda\n",
+    "from matplotlib.pyplot import imshow, show\n",
+    "from timeit import default_timer as timer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@cuda.jit(device=True)\n",
+    "def mandel(x, y, max_iters):\n",
+    "    \"\"\"Device function that calculates if a point belongs to Mandelbrot set\"\"\"\n",
+    "    c = complex(x, y)\n",
+    "    z = 0.0j\n",
+    "    for i in range(max_iters):\n",
+    "        z = z*z + c\n",
+    "        if (z.real*z.real + z.imag*z.imag) >= 4:\n",
+    "            return i\n",
+    "    return max_iters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@cuda.jit\n",
+    "def mandel_kernel(min_x, max_x, min_y, max_y, image, iters):\n",
+    "    \"\"\"CUDA kernel for Mandelbrot set calculation\"\"\"\n",
+    "    height = image.shape[0]\n",
+    "    width = image.shape[1]\n",
+    "    \n",
+    "    pixel_size_x = (max_x - min_x) / width\n",
+    "    pixel_size_y = (max_y - min_y) / height\n",
+    "    \n",
+    "    # Get the 2D thread position within the grid\n",
+    "    x, y = cuda.grid(2)\n",
+    "    \n",
+    "    # Make sure we stay within bounds\n",
+    "    if x < width and y < height:\n",
+    "        real = min_x + x * pixel_size_x\n",
+    "        imag = min_y + y * pixel_size_y\n",
+    "        image[y, x] = mandel(real, imag, iters)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a GPU array\n",
+    "gimage = np.zeros((1024, 1536), dtype=np.uint8)\n",
+    "\n",
+    "# Configure the blocks and grid\n",
+    "threadsperblock = (16, 16)\n",
+    "blockspergrid_x = (gimage.shape[1] + threadsperblock[0] - 1) // threadsperblock[0]\n",
+    "blockspergrid_y = (gimage.shape[0] + threadsperblock[1] - 1) // threadsperblock[1]\n",
+    "blockspergrid = (blockspergrid_x, blockspergrid_y)\n",
+    "\n",
+    "# Start the computation\n",
+    "start = timer()\n",
+    "d_image = cuda.to_device(gimage)\n",
+    "mandel_kernel[blockspergrid, threadsperblock](-2.0, 1.0, -1.0, 1.0, d_image, 20)\n",
+    "result_image = d_image.copy_to_host()\n",
+    "dt = timer() - start\n",
+    "\n",
+    "print(f\"Mandelbrot created on GPU in {dt:.6f} s\")\n",
+    "\n",
+    "# Display the result\n",
+    "imshow(result_image)\n",
+    "show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
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