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Initial proofreading #5

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Initial proofreading #5

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12 changes: 6 additions & 6 deletions Part1.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
"# 6.86x - Introduction to ML Packages (Part 1)\n",
"\n",
"This tutorial is designed to provide a bird's eye view of the ML packages landscape.\n",
"The goal is not to give an in-depth explanation of all the features of each packages, but rather demonstrate the purpose of a few widely used ML packages. For more details, we refer the reader to the packages' documentation and other online tutorials.\n",
"The goal is not to give an in-depth explanation of all the features of each package, but rather demonstrate the purpose of a few widely used ML packages. For more details, we refer the reader to the packages' documentation and other online tutorials.\n",
"\n",
"You can go through the Jupyter, Numpy and Matplotlib sections before the course starts, and then start studying the next sections after you have completed unit 1."
]
Expand All @@ -25,7 +25,7 @@
"source": [
"## Jupyter\n",
"\n",
"[Jupyter](https://jupyter.org) is not strictly speaking an ML package. It provides a browser front-end connected to an instance of IPython which allows REPL for quick testing, allows to create documents that intertwines code, output, images, and text. This is great for prototyping, demonstrations and tutorials, but terrible for actual coding. "
"[Jupyter](https://jupyter.org) is not strictly speaking an ML package. It provides a browser front-end connected to an instance of IPython which allows REPL for quick testing and allows us to create documents that intertwine code, output, images, and text. This is great for prototyping, demonstrations and tutorials, but terrible for actual coding. "
]
},
{
Expand Down Expand Up @@ -117,7 +117,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"[Numpy](http://www.numpy.org) is desiged to handle large multidimensional arrays and enable efficient computations with them. In the back, it runs pre-compiled C code which is much faster than, say, a Python `for` loop"
"[Numpy](http://www.numpy.org) is designed to handle large multidimensional arrays and enable efficient computations with them. In the back, it runs pre-compiled C code and does calculations in parallel which is much faster than, say, a Python `for` loop"
]
},
{
Expand All @@ -144,7 +144,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Numpy arrays can be indexed and sliced like regular python arrays"
"Numpy arrays can be indexed and sliced like regular Python arrays"
]
},
{
Expand Down Expand Up @@ -380,7 +380,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"When Numpy is asked to perform an operation between arrays of differents sizes, it \"broadcasts\" the smaller one to the bigger one."
"When Numpy is asked to perform an operation between arrays of different sizes, it \"broadcasts\" the smaller one to the bigger one."
]
},
{
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"name": "stdout",
"output_type": "stream",
"text": [
"Fitting 5 folds for each of 10 candidates, totalling 50 fits\n",
"Fitting 5 folds for each of 10 candidates, totaling 50 fits\n",
"[CV] C=1e-06 .........................................................\n",
"[CV] ................ C=1e-06, score=0.8424657534246576, total= 0.0s\n",
"[CV] C=1e-06 .........................................................\n",
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