updated notebooks for tutorial 2

tutorials/tutorial2/tutorial2-gradientdescent-extra.ipynb → tutorials/tutorial2/.ipynb_checkpoints/tutorial2-gradientdescent-extra-checkpoint.ipynb

@@ -4,7 +4,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Notebook 1b: Gradient Descent"
+    "## **Machine Learning for Physics and Astronomy**\n",
+    "\n",
+    "BSc program in Physics and Astronomy (Honours track), University van Amsterdam and Vrije Universiteit Amsterdam.\n",
+    "\n",
+    "**Academic year 2021-2022**. \n",
+    "\n",
+    "Course instructors:\n",
+    "\n",
+    "* Dr. Juan Rojo ([[email protected]](mailto:[email protected]))\n",
+    "\n",
+    "* Dr. Tommaso Giani ([[email protected]](mailto:[email protected]))\n",
+    "\n",
+    "* Mr. Ryan van Mastrigt ([[email protected]](mailto:[email protected]))\n",
+    "    \n",
+    "Lecture notes, tutorial notebooks, and other learning materials of the course can be found in its [GitHub repository](https://github.com/LHCfitNikhef/ML4PA)\n",
+    "\n",
+    "## Tutorial 2b: Optimisation with Stochastic Gradient Descent in 2D"
    ]
   },
   {
@@ -604,9 +620,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python mlreview",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "mlreview"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -618,9 +634,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

tutorials/tutorial2/tutorial2-gradientdescent.ipynb → tutorials/tutorial2/tutorial2a-gradientdescent-1D.ipynb

@@ -20,7 +20,7 @@
     "    \n",
     "Lecture notes, tutorial notebooks, and other learning materials of the course can be found in its [GitHub repository](https://github.com/LHCfitNikhef/ML4PA)\n",
     "\n",
-    "## Tutorial 2: Optimisation with Stochastic Gradient Descent\n",
+    "## Tutorial 2a: Optimisation with Stochastic Gradient Descent in 1D\n",
     "\n",
     "---\n"
    ]