100-days-of-machine-learning

binary-classification-of-images-using-cnn

The main goal was to build an CNN Architecture and explored the realms of CNN, how it extract the features from the input layer and manipulates the data and makes classification task extensively easy and produce an output from the hidden layer to the output layer

classification-of-machine-learning-model

A Classification of Machine Learning is defined as the Process of Predicting the output based on the input, where output variable is known as Dependent Variable and input variable is known as Independent Variable.

column-transformer

A column transformer is a technique which is used to encode the input features where optimize and easy to apply the column transformer technique.

data-analysis-using-data-from-datasets

Whenever we are going to work on any datasets , so we need to do by the classification of four categories to know and gain the useful information and insights of the dataset.

drowsiness-detection

A prototype which is a creative, compact and cost-effective solution which can seamlessly prevent dangerous accidents in commute by intelligently alerting the driver in lethargy and distraction using Computer Vision.

eda-using-univariate-analysis

EDA stands for Exploratory Data Analysis Where it is used to the independent analysis on the columns where each columns is considered as a variable

encoding-categorical-data

Encoding categorical data is a process used encode the categorical data which can be understandable by the Machine Learning Algorithms

feature-engineering

Feature Engineering is a process of extracting raw data and transforming to improve the perfomance of Machine Learning Model

feature-scaling-normalization-technique

Normalization is a technique which is often applied as a part of data preparation for Machine Learning the goal of normalization is to change the values of Numeric Columns to improve the efficiency of Machine Learning Model

fetching-data-from-an-api

Fetching Data From an API , It Simply Means Transfering the Data From Source to Destination and It Is also Called as Data Pipelines

frontend-basic-codes

fundamentals-of-r-language

R is an open-source programming language that is widely used as a statistical software and data analysis tool

hand-written-digit-recognition-using-cnn

The Goal was to build an CNN and explored how the neural network architectures classifies and works on the Multi-class Classification Problem

indian-sign-language-translator

k-nearest-neighbors-from-scratch

leetcode-questions

Collection of LeetCode/Geeks for Geeks questions to ace the coding interviews!

machine-learning-andrewng-solutions

All the solutions from the programming assignments of the Machine Learning Course in Coursera taught by Andrew NG, Professor of Stanford University

machine-learning-with-pipelines

machine-learning-without-pipelines

mathematical-transformer

A mathematical transformation is a process where we can apply the mathematical formulas on the input columns

mudith-nahata

numpy

NumPy is a Python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices.

online-machine-learning

A Online Machine Learning is used to train the data sequentially & Incrementally while dividing the each data in the production for prediction and Leaning is called as Online Machine Learning

pandas-data-frame-using-web-scraping

A collection of data from an Web browser and converting into a pandas data frames

pandas-profiling

A pandas profiling use to customize the report from data frames using a dataset and provides you the breif information of exploratory data analysis in the form of HTML format.

python

All Algorithms implemented in Python

static-gym-web-page

strivers-a2z-dsa-sheet

text-generator-using-lstm

Devloped a Model using LSTM which takes text data as an input and when user gives an input it predict the next word as an output based on the text data namely called "Next Word Predictor"