diff --git a/README.md b/README.md
index e9d8436..944a70c 100644
--- a/README.md
+++ b/README.md
@@ -2,9 +2,9 @@
 
 ## What is it?
 
-[Monolith](https://arxiv.org/abs/2209.07663) is a deep learning framework for large scale recommendation modeling. It introduces two important features which are crucial for advanced recommendation system: 
-* collisionless embedding tables guarantees unique represeantion for different id features
-* real time training captures the latest hotspots and help users to discover new intersts rapidly
+[Monolith](https://arxiv.org/abs/2209.07663) is a deep learning framework for large-scale recommendation modeling. It introduces two important features which are crucial for an advanced recommendation system: 
+* collisionless embedding tables guarantee unique representation for different ID features
+* real-time training captures the latest hotspots and helps users to discover new interests rapidly
 
 Monolith is built on the top of TensorFlow and supports batch/real-time training and serving.
 
@@ -19,7 +19,7 @@ https://discord.gg/QYTDeKxGMX
 
 ### Build from source
 
-Currently, we only support compilation on the Linux.
+Currently, we only support compilation on Linux.
 
 First, download bazel 3.1.0
 ```bash
@@ -29,7 +29,7 @@ wget https://github.com/bazelbuild/bazel/releases/download/3.1.0/bazel-3.1.0-ins
   rm bazel-3.1.0-installer-linux-x86_64.sh
 ```
 
-Then, prepare a python environment
+Then, prepare a Python environment
 ```bash
 pip install -U --user pip numpy wheel packaging requests opt_einsum
 pip install -U --user keras_preprocessing --no-deps
@@ -43,4 +43,4 @@ bazel run //monolith/native_training:demo --output_filter=IGNORE_LOGS
 
 ### Demo and tutorials
 
-There are a tutorial in [markdown/demo](markdown/demo) on how to run distributed async training, and few guides on how to use the `MonolithModel` API [here](markdown).  
\ No newline at end of file
+There is a tutorial in [markdown/demo](markdown/demo) on how to run distributed async training, and a few guides on how to use the `MonolithModel` API [here](markdown).