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Name: Tapendra Baduwal

Type: User

Bio: Machine Learning,Computer Vision, Natural Language Processing..

Location: Kathmandu Nepal

Blog: https://tapendrabaduwal.github.io/

Hello there, 👋 I am Tapendra Baduwal, currently working in the fields of Machine Learning, Data Science, and Business Intelligence, particularly focused on Feature Engineering, ML and DL Algorithms, Computer Vision, and Natural Language Processing. My ultimate career goal is to become an AI Researcher.

Tapendra Baduwal's Projects

attendance_system

Attendance System Using Face_recognation,OpenCv,Cmaker,dlib,numpy and other python inbuilt library such as os and datetime.

bank-loan-1

The bank and financial institution loan can be classified according to the overdue of the credit period.

chatbot-using-rasa-nlu

Rasa is an open source machine learning framework for automated text and voice-based conversations. Understand messages, hold conversations, and connect to messaging channels and APIs.

data-structure-and-algorithms

Data Structure and Algorithms

days_to_hours

This is simple calculation to convert days to hours unit.

e-commerce-customers

The main aim of this project is to use Linear regression in order to figure out how to maximize the Yearly Amount spent by the customers on the basis of some features like Length of Membership,Time on App,Average Session Length,Time on Website.

email-sms-spam-classifier

Spam classifier program in python which can tell whether a given message is spam or not!....I used FastAPI for an application programming interface. It helps to communicate between different programs.

face-module

Develop face module consists of various packages such as Face Capture, Face Annotation, Face Encoding, Face Detection and Face Recognition. The use of the OpenCV library with MediaPipe, Face Recognition library and the Streamlit Framework is carried out to accomplish this task.

facial_recognition_system_1

Facial Recognition System using python opencv,numpy and os library.

feature_engineering_1

Fundamental Techniques of Feature Engineering for Machine Learning · 1.Basic introduction · 2.Missing Data· 3.Handling Missing Data.4.Correlation matrix. 5.Identification of Outliers .6.Outlier Handling methods

feature_engineering_2

Feature Transformation and Scaling for Machine Learning. Techniques Present in Feature Transformation: Categorical features encoding,Mathematical transformation,Feature Scaling,Feature Selection. Types of categorical features encoding: (a) One-Hot Encoding,(b)Label/Ordinal Encoding Mathematical transformation (a)Logarithmic transformation,(b)Reciprocal transformation,(c)Square transformation,(d)Box-Cox transformation,(e)Yeo-Johnson transformation Feature Scaling (a)Normalization(Min-Max Scaling),(b)Standardization,(c)RobustScaler Scaling Feature Selection (a)Pearson's Correlation Coefficient matrix, (b)Chi-square Test

feature_engineering_3

Feature Engineering part 3. Different Types of Sampling Techniques,Techniques to Handle Imbalanced Datasets,Feature Creation in Machine Learning,Model Selection in Machine Learning,Machine Learning Pipeline.

impact-of-covid-19-on-nepalese-bank

IMPACT OF COVID-19 ON FINANCIAL PERFORMANCE OF NEPALESE COMMERCIAL BANK[ WITH REFERENCE TO RBB AND NABIL BANK LIMITED ]

knowledgegraph-nlp

Building a knowledge graph from the text scrapped from https://english.onlinekhabar.com/ articles

learning

lifelong learning notes.

mathematics

Linear Algebra ,Probability ,Statistics and Calculus for Machine Learning.

ml-and-dl-algorithms

Linear Regression,Polynomial Regression, Ridge Regression, Lasso Regression, Logistic Regression, Na ̈ıve Bayes, Decision Trees , Random Forest, AdaBoost, SVM, KNN, K-Means Clustering, PCA, Apriori, Q-Learning, Deep Learning(Deep Neural Network,Convolutional Neural Networks,Transformer).

tapendrabaduwal Goto Github PK

Tapendra Baduwal's Projects

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