In [22]:
!pip install tensorflow
Requirement already satisfied: tensorflow in /opt/conda/lib/python3.13/site-packages (2.20.0) Requirement already satisfied: absl-py>=1.0.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (2.3.1) Requirement already satisfied: astunparse>=1.6.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (1.6.3) Requirement already satisfied: flatbuffers>=24.3.25 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (25.9.23) Requirement already satisfied: gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (0.7.0) Requirement already satisfied: google_pasta>=0.1.1 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (0.2.0) Requirement already satisfied: libclang>=13.0.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (18.1.1) Requirement already satisfied: opt_einsum>=2.3.2 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (3.4.0) Requirement already satisfied: packaging in /opt/conda/lib/python3.13/site-packages (from tensorflow) (25.0) Requirement already satisfied: protobuf>=5.28.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (6.31.1) Requirement already satisfied: requests<3,>=2.21.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (2.32.5) Requirement already satisfied: setuptools in /opt/conda/lib/python3.13/site-packages (from tensorflow) (80.9.0) Requirement already satisfied: six>=1.12.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (1.17.0) Requirement already satisfied: termcolor>=1.1.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (3.2.0) Requirement already satisfied: typing_extensions>=3.6.6 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (4.15.0) Requirement already satisfied: wrapt>=1.11.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (2.0.1) Requirement already satisfied: grpcio<2.0,>=1.24.3 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (1.76.0) Requirement already satisfied: tensorboard~=2.20.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (2.20.0) Requirement already satisfied: keras>=3.10.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (3.12.0) Requirement already satisfied: numpy>=1.26.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (2.3.3) Requirement already satisfied: h5py>=3.11.0 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (3.15.1) Requirement already satisfied: ml_dtypes<1.0.0,>=0.5.1 in /opt/conda/lib/python3.13/site-packages (from tensorflow) (0.5.4) Requirement already satisfied: charset_normalizer<4,>=2 in /opt/conda/lib/python3.13/site-packages (from requests<3,>=2.21.0->tensorflow) (3.4.4) Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.13/site-packages (from requests<3,>=2.21.0->tensorflow) (3.11) Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.13/site-packages (from requests<3,>=2.21.0->tensorflow) (2.5.0) Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.13/site-packages (from requests<3,>=2.21.0->tensorflow) (2025.10.5) Requirement already satisfied: markdown>=2.6.8 in /opt/conda/lib/python3.13/site-packages (from tensorboard~=2.20.0->tensorflow) (3.10) Requirement already satisfied: pillow in /opt/conda/lib/python3.13/site-packages (from tensorboard~=2.20.0->tensorflow) (11.3.0) Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /opt/conda/lib/python3.13/site-packages (from tensorboard~=2.20.0->tensorflow) (0.7.2) Requirement already satisfied: werkzeug>=1.0.1 in /opt/conda/lib/python3.13/site-packages (from tensorboard~=2.20.0->tensorflow) (3.1.4) Requirement already satisfied: wheel<1.0,>=0.23.0 in /opt/conda/lib/python3.13/site-packages (from astunparse>=1.6.0->tensorflow) (0.45.1) Requirement already satisfied: rich in /opt/conda/lib/python3.13/site-packages (from keras>=3.10.0->tensorflow) (14.2.0) Requirement already satisfied: namex in /opt/conda/lib/python3.13/site-packages (from keras>=3.10.0->tensorflow) (0.1.0) Requirement already satisfied: optree in /opt/conda/lib/python3.13/site-packages (from keras>=3.10.0->tensorflow) (0.18.0) Requirement already satisfied: markupsafe>=2.1.1 in /opt/conda/lib/python3.13/site-packages (from werkzeug>=1.0.1->tensorboard~=2.20.0->tensorflow) (3.0.3) Requirement already satisfied: markdown-it-py>=2.2.0 in /opt/conda/lib/python3.13/site-packages (from rich->keras>=3.10.0->tensorflow) (4.0.0) Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /opt/conda/lib/python3.13/site-packages (from rich->keras>=3.10.0->tensorflow) (2.19.2) Requirement already satisfied: mdurl~=0.1 in /opt/conda/lib/python3.13/site-packages (from markdown-it-py>=2.2.0->rich->keras>=3.10.0->tensorflow) (0.1.2)
In [23]:
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Flatten, Dense
from tensorflow.keras.utils import to_categorical
/opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/attr_value.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/tensor.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/resource_handle.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/tensor_shape.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/types.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/full_type.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/function.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/node_def.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/op_def.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/graph.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/graph_debug_info.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/versions.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/protobuf/config.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at xla/tsl/protobuf/coordination_config.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/cost_graph.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/step_stats.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/allocation_description.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/framework/tensor_description.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/protobuf/cluster.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn( /opt/conda/lib/python3.13/site-packages/google/protobuf/runtime_version.py:98: UserWarning: Protobuf gencode version 5.28.3 is exactly one major version older than the runtime version 6.31.1 at tensorflow/core/protobuf/debug.proto. Please update the gencode to avoid compatibility violations in the next runtime release. warnings.warn(
In [9]:
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten
from tensorflow.keras.utils import to_categorical
In [18]:
(x_train,y_train),(x_test,y_test)=mnist.load_data()
x_train,x_test=x_train/255,x_test/255
y_train= to_categorical(y_train,10)
y_test= to_categorical(y_test,10)
In [20]:
plt.figure(figsize=(10,10))
for i in range(9):
plt.subplot(3,3,i+1)
plt.imshow(x_train[i],cmap='gray')
plt.title("Digit:{}".format(np.argmax(y_train[i])))
plt.axis('off')
plt.show()
In [36]:
model = Sequential([
Flatten(input_shape =(28, 28)),
Dense(128, activation='relu'),
Dense(64, activation='relu'),
Dense(10, activation='softmax')
])
In [32]:
model = tf.keras.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10, activation='softmax')
])
/opt/conda/lib/python3.13/site-packages/keras/src/layers/reshaping/flatten.py:37: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead. super().__init__(**kwargs)
In [34]:
model.compile(optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy'])
In [51]:
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = x_train.astype('float32') / 255.0 # Normalize to [0, 1]
x_test = x_test.astype('float32') / 255.0
In [37]:
mod = model.fit(x_train,y_train,
epochs=10,
batch_size=32,validation_data=(x_test,y_test))
--------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[37], line 1 ----> 1 mod = model.fit(x_train,y_train, 2 epochs=10, 3 batch_size=32,validation_data=(x_test,y_test)) NameError: name 'x_train' is not defined
In [34]:
test_loss,test_acc = model.evaluate(x_test, y_test)
print("Test accuracy",test_acc)
--------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[34], line 1 ----> 1 test_loss,test_acc = model.evaluate(x_test, y_test) 2 print("Test accuracy",test_acc) NameError: name 'x_test' is not defined
In [56]:
predictions = model.predict(x_test[:5])
for i in range(5):
plt.imshow(x_test[i],cmap='gray')
plt.title("Predicted:{},Actual:{}".format(np.argmax(predictions[i]),np.argmax(y_test[i])))
plt.axis('off')
plt.show()
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 63ms/step
In [27]:
from PIL import Image
import numpy as np
import tensorflow as tf
from tensorflow import keras
img_path='forML.png'
img=Image.open('images/forML.png').convert('L')
img=img.resize((28,28))
img_array=np.array(img)
img_array=img_array/255.0
img_array=img_array.reshape(1,28,28)
In [35]:
predictions = model.predict(img_array)
predicted_digit=np.argmax(predictions)
print("Predicted Digit:",predicted_digit)
plt.imshow(img,cmap='gray')
plt.title(f"Predicted Digit: {predicted_digit}")
plt.axis('off')
plt.show()
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 61ms/step Predicted Digit: 3
In [ ]: