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This is a basic introduction of gRPC.

Benefits of gRPC

gRPC uses protocol buffers and HTTP2, which will help the service communications to be much faster, and use less resources.

Protocol Buffers vs JSON

By using protocol buffers, we can achieve faster and more efficient communication, especially for devices with slower CPUs:

  1. Payload Size: To store the…

This is the first tutorial of this series, which covers the basic concepts of Kafka

Basic Concept — Data Topics

  1. Topic: A particular stream of data, identified by the topic name.
  2. Partition: Topic splits into partitions; Each partition is a queue of messages.
  3. Offset: The incremental id assigned to the message in the partition.


  1. Offset…

In this blog, we will discuss an interview question asked by Google.

In this post, we are going to discuss the leetcode problem no. 1055 — Shortest Way to Form String, which is recently asked in Google interviews.

Firstly, we will try to solve the problem with brute force method…

Recent interview question asked by Google and Amazon.

In this post, we are going to discuss the leetcode problem no. 253 — Meeting Rooms II. This problem is recently asked in Google and Amazon interviews.

Problem Analysis

The input of the problem is a list of meeting schedules. Each meeting schedule…

This is an introduction to dynamic array and its implementation

An array is a contiguous area of memory of equal-size elements. Array length is usually fixed, which means you need to specify the number of elements your array can hold ahead of time.

A dynamic array is an array which…

In this post, I will discuss details about Gradient Descent and Back-propagation in neural networks, and will help you to understand why there is Vanishing Gradient Problem. In my earlier post (How to implement Gradient Descent in Python), I discussed python implementation of Gradient Descent. …

Gradient Descent is the most important concept in Neural Networks. In this tutorial, I am going to show you how to implement it in Python. I hope this tutorial can help you to build a better understanding about how gradient descent works, and how it helps to improve model accuracy.

Data Pre-Processing

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