Update app.py

app.py

@@ -35,77 +35,61 @@ if selected == 'About me':
     st.write('I have been learning Machine learning since 2021 and have Made more than 50 projects in the field of Machine Learning')
     st.write('---')
 if selected == 'Tools and Experience':
-
-    st.write('# Below are the tools I use to train AI and the Machine Learning and Deep Learning models I have expertise in')
+    st.header('Tools and Experience')
+    col1,col2 = st.columns(2)
+    with col1:
+        st.write('Below are the tools I use to train AI and the Machine Learning and Deep Learning models I have expertise in')
+    with col2:
+        st_lottie(lottiemaker('Tools.json'),speed=1,width=200,height=200)
     st.write('# Tools I use to train AI')
     col1,col2,col3,col4 = st.columns(4)
     with col1:
-        st.image(loadimg('python.jpg'),use_column_width=False)
-        st.write("Python")
+        st.button('Python')
     with col2:
-        st.image(loadimg('tensorflow.png'),use_column_width=False)
-        st.write('Tensorflow')
+        st.button('Tensorflow')
     with col3:
-        st.image(loadimg('numpy.png'),use_column_width=False)
-        st.write('Numpy')
-
+        st.button('Numpy')
     with col4:
-        st.image(loadimg('keras.png'),use_column_width=False)
-        st.write('Keras')
+        st.button('Keras')
         
     _,col1,col2,col3,_ = st.columns(5)
     with col1:
-        st.image(loadimg('matplotlib.png'),use_column_width=False)
-        st.write('Matplotlib')
+        st.button("Matplotlib")
     with col2:
-        st.image(loadimg('kaggle.png'),use_column_width=False)
-        st.write('Kaggle')
+        st.button('Pandas')
     with col3:
-        st.image(loadimg('pandas.png'),use_column_width=False)
-        st.write('Pandas')
+        st.button('Kaggle')
 
     st.write('# I have Experience in')
     col1,col2,col3,col4 = st.columns(4)
     with col1:
-        st.image(loadimg('ANN.png'),use_column_width=False)
-        st.write("Artificial Neural Network")
+        st.button('Artificial Neural Network')
     with col2:
-        st.image(loadimg('cnn.jpg'),use_column_width=False)
-        st.write("Convolutional Neural Network")
+        st.button("Convolutional Neural Network")
     with col3:
-        st.image(loadimg('GAN.png'),use_column_width=False)
-        st.write("Deep Convolutional Genertive Adversarial Network")
+        st.button("Deep Convolutional Genertive Adversarial Network")
     with col4:
-        st.image(loadimg('Cyclegan.jpg'),use_column_width=False)
-        st.write("Cycle Consistent Generative Adversarial Network") 
+        st.button("Cycle Consistent Generative Adversarial Network") 
 
     col1,col2,col3,col4 = st.columns(4)
     with col1:
-        st.image(loadimg('pix2pix.png'),use_column_width=False)
-        st.write("Pix2Pix")
+        st.button("Pix2Pix")
     with col2:
-        st.image(loadimg('Yolo.jpg'),use_column_width=False)
-        st.write("Object Detection using YOLO")
+        st.button("Object Detection using YOLO")
     with col3:
-        st.image(loadimg('Unet.png'),use_column_width=False)
-        st.write("Unet model for semantic segmentation")
+        st.button("Unet model for semantic segmentation")
     with col4:
-        st.image(loadimg('segyolo.jpg'),use_column_width=False)
-        st.write("Instance Segmentation using YOLO")  
+        st.button("Segmentation using YOLO")  
 
     col1,col2,col3,col4 = st.columns(4)
     with col1:
-        st.image(loadimg('Linear.png'),use_column_width=False)
-        st.write("Linear Regression")
+        st.button("Linear Regression")
     with col2:
-        st.image(loadimg('logistic.png'),use_column_width=False)
-        st.write("Logistic Regression")
+        st.button("Logistic Regression")
     with col3:
-        st.image(loadimg('naive bayes.png'),use_column_width=False)
-        st.write("Naive Bayes Classifier")
+        st.button("Naive Bayes Classifier")
     with col4:
-        st.image(loadimg('DecisionTree.png'),use_column_width=False)
-        st.write("Decision Tree Classiifer")   
+        st.button("Decision Tree Classiifer")   
 
 elif selected == 'Projects':
     st.write(selected)