DEV Community: Ujjawal Patel

becoming a full stack developer

Ujjawal Patel — Mon, 08 Dec 2025 17:04:04 +0000

made a simple website using html and css building my own music website but is currently facing many issues like i need liscense of the music legally which is very tough to get

dropped ml for some time but will be backing up soon

Becoming full stack developer

Ujjawal Patel — Wed, 03 Dec 2025 10:38:39 +0000

Sorry guys became inconsistent due to exams bus back again and understood the js concepts related t async
1.setTimeout()
2.clearTimeout()
3.setInterval()
4.clearInterval()
Will be crushing things forward
Welcome back !!

Day 12 of becoming a full stack developer

Ujjawal Patel — Sat, 22 Nov 2025 03:30:49 +0000

Trying to boost in everything in ml and js
Learnt about feature scaling specifically standardisation the guy ever did ml will know about it fs

Also did some of my hobby work 🥰

Day 10 and 11 of becoming full stack developer

Ujjawal Patel — Thu, 20 Nov 2025 01:54:43 +0000

Completed python essentials 1 from cisco course and tried understanding data using Ydata profiling

Day 6,7,8 and 9 of becoming a full stack developer

Ujjawal Patel — Tue, 18 Nov 2025 01:57:29 +0000

Completed almost 25 videos from campusx (100 days of ML)

Dropped js for now for some time

Becoming a full stack developer (Ml Engineer) day 5

Ujjawal Patel — Thu, 13 Nov 2025 20:25:54 +0000

Tried some of the data cleaning methods and practiced numpy and pandas will update you soon..

Actually I know I did bare minimum I could do today because of you know my procrastination but I promise I will make up the today's thing the next day

Becoming a Full stack developer Day 4

Ujjawal Patel — Tue, 11 Nov 2025 20:45:58 +0000

Hey there I came back with my update
Tried completing events although there are a lot of thing so I will cover it tomorrow but covered many thind like addEventListner, onclick, event propogation and prevent default

And in ml I studied reading methods from campusx
Studied concepts which are commonly used or encountered while dealing with csv file

Reading data from the CSV file you uploaded

Import data from server and then raeding

Reading a tsv file

Index column parameter

when there are two rows present for the index so we can remove one of them

Header parameter

when you column headers are treated as one column

Use column parameter

only how many data you want -> only that much data will be imported how much data you want rest will be deleted consider we want only some selected columns

skip rows

whichever paticular rows you want you can enter them to not allow to get imported

n rows parameter

one the number you mention will be imported

Encoding Parameter

Skip bad lines

skips those data which has inconsistency

D type parameters

if you want to change any datatype

Handling dates

whenever we use read csv by default date columns are passed as strings so we cannot use date functionalities

convertors

na values parameter

sometimes in place of NaN values there are many other values such as / . etc so we need to specify which all values in consider as NaN

Loading huge dataset in chunks

Becoming a Full stack developer Day 3

Ujjawal Patel — Mon, 10 Nov 2025 17:02:25 +0000

Tried to complete events in js from chai and code but the way super unproductive although i covered

Event listeners
On click
On mouseover etc

Also covered some part of data science coursse from code with Harry
Completed Understanding the Conda Environment playlist
Understood

conda environmnet
How to create virtual environment (conda create -n myenv)
Accepting some specific versions eg (conda create -n myenv python=3.6)
Understood the jupyter notebook and jupiter lab although both perform the same task but jupyter notebook is a bit light while jupytr lab is bit heavier and also has more functionalities and flexibility unlike jupyter notebook

Becoming a Full Stack Developer Day 2

Ujjawal Patel — Sun, 09 Nov 2025 19:10:53 +0000

Made 4 mini projects using html, css and js

Guessing number game generated my math random module
color match background changer on click
Simple clock
BMI Calculator

learnt about anaconda and mini conda

Anaconda - Full distribution with hundreds of packages for data science and machine learning
Mini Conda - Lightweight version of anaconda

Becoming a Full Stack developer Day 1

Ujjawal Patel — Sat, 08 Nov 2025 19:44:35 +0000

Learnt DOM in js from Chai and Code
Learnt DATA SCIENCE LIFECYCLE from CWH DS course

Problem Definition - the first step is to understand the problem what exactly what do you want to solve
Data Collection - it is the process of collecting data from various sources such as Web Scraping, Databases, Third Party Data, APIs etc
Data Cleaning - it is the process of cleaning data by removing or editing the inaccurate or incomplete data using various python libraries such as pandas numpy ( in the initial state data is known as data dump ) a data scientist spends around 80% of his time in data cleaning
Data Exploration - understanding the data and finding the relations and patterns in the data using Matplotlib, Seaborn
Model building - Creating and training the model for predictions or decision making the models can be a simple python program to a complex machine learning model eg : Scikit learn , Tensor flow, PyTorch
Model Evaluation - it is the process of checking how accurate the model is , it is done by using some data for evaluation and some data for training the model
Deployment - grounding the model in to the real world or the production system using Flask, Fast API, React
Communication and reporting - sharing insights at the end of the day
Maintenance and Evaluation - Keeping the model updated and accurate as the inaccurate data may lead to inconsistency in the result