diff --git a/README.md b/README.md
index ac278f7..5e20ebe 100644
--- a/README.md
+++ b/README.md
@@ -1,702 +1 @@
-
-### Import Libraries
-
-
-```python
-import pandas as pd
-import numpy
-import matplotlib.pyplot as plt
-%matplotlib inline
-```
-
-### Read the CSV file
-
-
-```python
-df = pd.read_csv("E://Telugu Character Recogniton//CSV_dataset//CSV_datasetsix_vowel_dataset_with_class.csv")
-
-df.head()
-```
-
-
-
-
-<div>
-<style scoped>
-    .dataframe tbody tr th:only-of-type {
-        vertical-align: middle;
-    }
-
-    .dataframe tbody tr th {
-        vertical-align: top;
-    }
-
-    .dataframe thead th {
-        text-align: right;
-    }
-</style>
-<table border="1" class="dataframe">
-  <thead>
-    <tr style="text-align: right;">
-      <th></th>
-      <th>pixel0</th>
-      <th>pixel1</th>
-      <th>pixel2</th>
-      <th>pixel3</th>
-      <th>pixel4</th>
-      <th>pixel5</th>
-      <th>pixel6</th>
-      <th>pixel7</th>
-      <th>pixel8</th>
-      <th>pixel9</th>
-      <th>...</th>
-      <th>pixel775</th>
-      <th>pixel776</th>
-      <th>pixel777</th>
-      <th>pixel778</th>
-      <th>pixel779</th>
-      <th>pixel780</th>
-      <th>pixel781</th>
-      <th>pixel782</th>
-      <th>pixel783</th>
-      <th>class</th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <th>0</th>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>252</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>1</td>
-    </tr>
-    <tr>
-      <th>1</th>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>1</td>
-    </tr>
-    <tr>
-      <th>2</th>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>1</td>
-    </tr>
-    <tr>
-      <th>3</th>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>1</td>
-    </tr>
-    <tr>
-      <th>4</th>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>253</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>1</td>
-    </tr>
-  </tbody>
-</table>
-<p>5 rows × 785 columns</p>
-</div>
-
-
-
-
-```python
-df.tail()
-```
-
-
-
-
-<div>
-<style scoped>
-    .dataframe tbody tr th:only-of-type {
-        vertical-align: middle;
-    }
-
-    .dataframe tbody tr th {
-        vertical-align: top;
-    }
-
-    .dataframe thead th {
-        text-align: right;
-    }
-</style>
-<table border="1" class="dataframe">
-  <thead>
-    <tr style="text-align: right;">
-      <th></th>
-      <th>pixel0</th>
-      <th>pixel1</th>
-      <th>pixel2</th>
-      <th>pixel3</th>
-      <th>pixel4</th>
-      <th>pixel5</th>
-      <th>pixel6</th>
-      <th>pixel7</th>
-      <th>pixel8</th>
-      <th>pixel9</th>
-      <th>...</th>
-      <th>pixel775</th>
-      <th>pixel776</th>
-      <th>pixel777</th>
-      <th>pixel778</th>
-      <th>pixel779</th>
-      <th>pixel780</th>
-      <th>pixel781</th>
-      <th>pixel782</th>
-      <th>pixel783</th>
-      <th>class</th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <th>1195</th>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>6</td>
-    </tr>
-    <tr>
-      <th>1196</th>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>6</td>
-    </tr>
-    <tr>
-      <th>1197</th>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>6</td>
-    </tr>
-    <tr>
-      <th>1198</th>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>254</td>
-      <td>255</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>6</td>
-    </tr>
-    <tr>
-      <th>1199</th>
-      <td>254</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>252</td>
-      <td>254</td>
-      <td>255</td>
-      <td>254</td>
-      <td>254</td>
-      <td>254</td>
-      <td>...</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>255</td>
-      <td>6</td>
-    </tr>
-  </tbody>
-</table>
-<p>5 rows × 785 columns</p>
-</div>
-
-
-
-
-```python
-
-```
-
-### Reading First instance
-
-
-```python
-df.iloc[2]
-
-```
-
-
-
-
-    pixel0      255
-    pixel1      254
-    pixel2      255
-    pixel3      255
-    pixel4      255
-    pixel5      255
-    pixel6      254
-    pixel7      255
-    pixel8      254
-    pixel9      255
-    pixel10     255
-    pixel11     255
-    pixel12     255
-    pixel13     253
-    pixel14     255
-    pixel15     254
-    pixel16     254
-    pixel17     255
-    pixel18     254
-    pixel19     255
-    pixel20     254
-    pixel21     255
-    pixel22     255
-    pixel23     254
-    pixel24     255
-    pixel25     255
-    pixel26     255
-    pixel27     255
-    pixel28     255
-    pixel29     253
-               ... 
-    pixel755    255
-    pixel756    255
-    pixel757    255
-    pixel758    255
-    pixel759    255
-    pixel760    255
-    pixel761    255
-    pixel762    255
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-    pixel765    255
-    pixel766    255
-    pixel767    255
-    pixel768    255
-    pixel769    255
-    pixel770    255
-    pixel771    255
-    pixel772    255
-    pixel773    255
-    pixel774    255
-    pixel775    255
-    pixel776    255
-    pixel777    255
-    pixel778    255
-    pixel779    255
-    pixel780    255
-    pixel781    255
-    pixel782    255
-    pixel783    255
-    class         1
-    Name: 2, Length: 785, dtype: int64
-
-
-
-### Reshaping into 28X28 array
-
-
-```python
-pix=[]
-for i in range(784):
-    pix.append('pixel'+str(i))
-features=pix
-X = df.loc[:, features].values
-y=df.loc[:,'class'].values
-X[0]
-```
-
-
-
-
-    array([255, 255, 254, 255, 255, 255, 252, 255, 255, 255, 254, 255, 253,
-           255, 255, 254, 253, 255, 255, 253, 255, 255, 255, 253, 255, 255,
-           255, 255, 254, 255, 255, 254, 255, 255, 255, 254, 255, 255, 255,
-           253, 255, 254, 254, 255, 255, 252, 255, 254, 254, 255, 253, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 253, 253, 255, 254, 253,
-           255, 252, 253, 255, 255, 253, 255, 255, 255, 255, 255, 255, 254,
-           255, 250, 255, 255, 255, 255, 255, 253, 253, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 252, 254, 252, 255, 255, 255, 254, 253,
-           255, 253, 253, 255, 255, 255, 255, 255, 254, 255, 255, 252, 254,
-           168,   1,   0,   0, 255, 255, 255, 255, 253, 255, 255, 255, 255,
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-           255, 254,   0, 253, 254, 255, 244,   0, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 254, 255, 201, 255, 254, 255,  95, 252,
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-             0, 253, 253, 253, 255,   0, 255, 255, 253, 255, 255, 196, 255,
-           253, 255, 255, 255, 255, 255, 255, 255, 250, 255, 126, 255,   2,
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-           253, 255, 255, 252, 255, 255, 255, 255, 255, 254, 255, 254, 125,
-           254, 254, 255, 255, 254, 254, 255, 253, 252,   2, 255, 253, 255,
-           254, 254, 255, 252, 255, 255, 255, 255, 255, 255, 255, 255, 253,
-           255, 126, 255, 251, 251, 254, 255, 253, 255, 255, 255, 215,   4,
-           253, 255, 255, 255,  85, 253, 252, 254, 255, 255, 255, 255, 255,
-           255, 255, 255, 254, 163, 255, 255, 255, 255,   0,   0,   0,   4,
-             0,   0,   3, 250, 255, 255,   0, 255, 255, 255, 253, 255, 255,
-           255, 255, 255, 255, 249, 255,   1, 251, 255, 253, 254, 254, 255,
-           255, 251, 255, 255, 255, 255, 255, 255,   1, 254, 255, 251, 255,
-           255, 255, 255, 255, 253, 255, 255, 254,   9, 254, 255, 254, 255,
-           255, 255, 254, 255, 254, 254, 255, 253, 255, 237,  85, 255, 253,
-           255, 254, 255, 255, 255, 255, 255, 255, 252, 255, 254,   2, 253,
-           255, 253, 255, 253, 255, 255, 253, 255, 255, 255, 255,   0, 253,
-           255, 255, 255, 253, 255, 255, 255, 255, 253, 253, 255, 255, 253,
-           178,   0, 255, 255, 252, 255, 253, 252, 255, 253, 253, 255,   2,
-           255, 255, 255, 252, 255, 255, 255, 255, 255, 255, 255, 255, 252,
-           253, 255, 253,  14,   1,   0, 252, 255, 255, 255, 255, 254, 255,
-             0, 132, 251, 254, 254, 255, 252, 255, 255, 255, 255, 255, 255,
-           253, 255, 255, 255, 255, 254, 252, 254,  10,   1,   0,   0,   0,
-             0,   5, 255, 255, 255, 255, 254, 253, 255, 253, 255, 255, 255,
-           255, 254, 255, 251, 255, 255, 255, 252, 255, 255, 253, 255, 255,
-           255, 255, 254, 254, 255, 253, 251, 255, 253, 255, 255, 253, 255,
-           255, 255, 255, 254, 255, 255, 255, 255, 253, 255, 253, 252, 255,
-           255, 255, 254, 254, 255, 254, 253, 255, 255, 252, 255, 255, 253,
-           255, 255, 255, 255, 255, 254, 255, 255, 255, 255, 255, 252, 255,
-           255, 252, 255, 253, 255, 253, 255, 255, 255, 255, 255, 255, 254,
-           254, 253, 255, 255, 255, 255, 255, 255, 255, 255, 253, 253, 255,
-           255, 255, 251, 255, 255, 254, 255, 255, 254, 255, 254, 255, 252,
-           255, 254, 255, 255, 253, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
-           255, 255, 255, 255], dtype=int64)
-
-
-
-
-```python
-imarray = numpy.asfarray(X[11]).reshape((28,28))
-```
-
-
-```python
-imarray
-```
-
-
-
-
-    array([[255., 252., 255., 255., 255., 252., 255., 255., 255., 255., 252.,
-            255., 253., 255., 254., 255., 255., 252., 255., 254., 255., 255.,
-            255., 254., 255., 255., 255., 255.],
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-           [255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255.],
-           [255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255.],
-           [255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255.],
-           [255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255., 255., 255., 255., 255., 255.,
-            255., 255., 255., 255., 255., 255.]])
-
-
-
-### Plotting the reconstructed image
-
-
-```python
-print('After Converting values ie.., [0-255] in between [0-1] : ')
-imarray=255-imarray
-plt.imshow(imarray,cmap=plt.cm.binary);
-# print(imarray)
-```
-
-    After Converting values ie.., [0-255] in between [0-1] : 
-    
-
-
-![png](output_13_1.png)
-
-
-
-```python
-# nimg = tf.keras.utils.normalize(imarray,axis=0)
-nimg=imarray/255.0
-print('After Converting values ie.., [0-255] in between [0-1] : ')
-plt.imshow(nimg,cmap=plt.cm.binary);
-```
-
-    After Converting values ie.., [0-255] in between [0-1] : 
-    
-
-
-![png](output_14_1.png)
-
-
-
-```python
-def row2img(pos):
-    return numpy.asfarray(X[pos]).reshape((28,28))
-
-f, (ax1, ax2, ax3) = plt.subplots(1, 3, sharey=True)
-f.suptitle("Images with respective Classes(1-3)")
-ax1.set_title('Class: 1')
-ax1.imshow(255-row2img(26),cmap=plt.cm.binary);
-ax2.set_title('Class: 2')
-ax2.imshow(255-row2img(222),cmap=plt.cm.binary);
-ax3.set_title('Class: 3')
-ax3.imshow(255-row2img(444),cmap=plt.cm.binary);
-
-```
-
-
-![png](output_15_0.png)
-
-
-
-```python
-f, (ax1, ax2, ax3) = plt.subplots(1, 3, sharey=True)
-f.suptitle("Images with respective Classes(4-6)")
-ax1.set_title('Class: 4')
-ax1.imshow(255-row2img(666),cmap=plt.cm.binary);
-ax2.set_title('Class: 5')
-ax2.imshow(255-row2img(999),cmap=plt.cm.binary);
-ax3.set_title('Class: 6')
-ax3.imshow(255-row2img(1111),cmap=plt.cm.binary);
-```
-
-
-![png](output_16_0.png)
-
-
-
-```python
-
-```
+## Telugu Character Recognition