sheezashabbir Goto Github PK

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Name: Sheeza

Type: User

Company: @upwork

Bio: I am a talented software Engineer ad Data Scientist with a strong desire to build a career. Passionate and self-motivated individuals to succeed.

Location: Pakistan

Blog: www.linkedin.com/in/software-engineer-sheeza-shabir

Sheeza's Projects

90_animal_detection-using-vit

The "Animal Detection Using VIT Transformers with 97% Testing Accuracy" project is a focused and achievable initiative aimed at building an accurate animal detection system. Leveraging Vision Transformer (VIT) models, this project is dedicated to the specific goal of achieving a high testing accuracy of 97% in identifying.

android_offline_externaldb_dictionary

Android_offline_ExternalDB_Dictionary

bagofwords-computer-vision-

1-Bag of SIFT representation and nearest neighbor classifier

bert_for_disaster_data_text-classification

Disasters Classification using Bert

cannyedgedetection-computer-vision-

There are some basic steps for the implementation of a Canny edge detector. 1. Generation of Masks 2. Applying Masks to Images 3. Compute gradient magnitude 4. Compute gradient Direction 5. Non-Maxima Suppression 6. Hysteresis Thresholding

cherry_leaf_health_detector_app

The "Cherry Leaf Health Detector" is a comprehensive repository housing a sophisticated Streamlit web application designed to assess the health of cherry leaves by distinguishing between healthy leaves and those affected by powdery mildew.

custom_dialog_withvideo

Android studio Custom dialog box work video.

cyber-security-salaries-dataset-and-multivariable-regression

Cyber Security Salaries Dataset and Multivariable Regression

cyber_security_salaries_data_analysis

Exploratory Data Analysis on Cyber Security Dataset

data_visualization-using-utilmy

Data_Visualization using utilmy

download-books-in-python

One can download any book using this code of python

eda-on-crisismdd-dataset

Exploratory Data Analysis on CrisisMDD Dataset

exploratory-data-analysis

Exploratory Data Analysis on Complex Data with Different plots Visualization

facerecognition-using-cnn-custom-model

Recognizing Human faces and predicting Who is this person? It is a classification problem i.e. classify the digital image of a human face against a database of faces and tell who exactly the person is. For this purpose I am using Celebrity Dataset. Implementation of a custom model that gives 99% accuracy on the test data.

faceverification-using-cnn-custom-model

Implementing a model that can verify if two images belongs to same personality or not. Answer the question "Is this the claimed person?" It is a 1:1 matching problem i.e. given a face your task is to compare the candidate face to another and verify whether it is a match or not. My custom CNN model has achieved marvelous performance on the dataset.

harriscornerdetection-computer-vision-

Harris Corner Detection with complete implementation.

multimodel_huggingface-swin-transformer

A multimodal that uses both text and Images to tells what will be the expected emotion of the viewer of the news.

multitasklearning-multi-label-classification-using-cnn-

Training a new classification network which should tell the identity label of an image and also be able to classify: ● Gender as Male/Female ● Wearing Glasses/ Not Wearing Glasses ● Smiling/ Not Smiling ● Wearing hat/ not wearing hat ● young/old. As we need 5 outputs from a single input. The custom CNN model consists of NN architecture with 5 heads return my the model. My model performance in Multilabel classification task is totally remarkable.

nested-dictionaries-to-dataframe

Converting Columns with nested dictionaries to Data frame Separate columns

preprocessing-and-classification-on-lending-club-dataset

Lending Club is a lending platform that lends money to people in need at an interest rate based on their credit history and other factors. In this blog, we will analyze this data and pre-process it based on our need and build a machine learning model that can identify a potential defaulter based on his/her history of transactions with Lending Club. This dataset contains 42538 rows and 144 columns. Out of these 144 columns, many columns have null values in majority.

python-code

Python code tutorial

python-data-science-work

Python Data Science

python-data-structure

Python Data Structure

python-files-read-and-write

Reading and writing files in python.

rnn-classifying-name-at-character-level

A character-level RNN reads words as a series of characters - outputting a prediction and “hidden state” at each step, feeding its previous hidden state into each next step. We take the final prediction to be the output, i.e. which class the word belongs to.

sheezashabbir Goto Github PK

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