anandprems
Python | Machine Learning | Deep Learning
Assistant Professor | Researcher | FreelancerChennai
Pinned Repositories
anandprems
Artificial-Neural-Network-in-Python-from-scratch
cnn
Computer-Programming-Python
Data-Science-Interview-Question-and-Answers
In this repository i am sharing some important questions related to Data Science, which was shared by ineuron edu company. While preparing for Data Science interview this documents plays important role
Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
Data_Science_2024
Embedded-C-Programmings
mitbih_cnn
Dataset: https://www.physionet.org/content/mitdb/1.0.0/
ML-For-Beginners-2024
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
anandprems's Repositories
anandprems/Computer-Programming-Python
anandprems/mitbih_cnn
Dataset: https://www.physionet.org/content/mitdb/1.0.0/
anandprems/Artificial-Neural-Network-in-Python-from-scratch
anandprems/Embedded-C-Programmings
anandprems/anandprems
anandprems/cnn
anandprems/Data-Science-Interview-Question-and-Answers
In this repository i am sharing some important questions related to Data Science, which was shared by ineuron edu company. While preparing for Data Science interview this documents plays important role
anandprems/Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
anandprems/Data_Science_2024
anandprems/ML-For-Beginners-2024
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
anandprems/SVM_Classification_Regression
anandprems/3_Statistics_MoCT_Mean
anandprems/autoencoders_python
In this repository i will be explaining all about autoencoders, types and its functions
anandprems/BECE101-Basic-Electronics-VIT
In this repository I am uploading the materials used for the subject BECE101 Basic Electronics in particular.
anandprems/Classification---30-model---Pyforest
In this repository, i discussed about by using Pyforest command we can easily retrive around 40 differernt model's Accuracy, balanced accuracy, AUC-ROC, F1 score and time taken values, without spending much time in coding. I am not saying this is the best way to explore but still this is one kind of way to do coding
anandprems/chaf_tech_science_cmc
anandprems/Computer-Vision-Decoding-the-Visual-World
anandprems/eda_1
Some basic idea about Exploratory Data Analysis steps
anandprems/git_practice_session
Together, Git and GitHub form a powerful combination for modern software development. Git provides the robust version control necessary for managing changes, while GitHub offers a collaborative platform with additional tools and features to streamline the development process.
anandprems/hgb_classifier
anandprems/histogram_gradient_boosting_classifier
So here, we are using histogram based gradient boosting algorithm for PTB dataset which is acquired from Physionet website after doing some preprocessing. Dataset can be downloaded from, https://www.kaggle.com/shayanfazeli/heartbeat
anandprems/LightGBM_ML_Algorithm
Are you tired of slow and inaccurate machine learning algorithms? Do you struggle with large datasets and high-dimensional features? Look no further than LightGBM, a powerful and efficient machine learning algorithm that can handle these challenges and more.
anandprems/matplotlib_python
anandprems/physionet_ptbdb_ann
anandprems/Python_RAM_
anandprems/Regression---40model---Pyforest
In this repository, i discussed about by using Pyforest command we can easily retrive around 40 differernt model's Adjusted R2, R2, RMSE and time taken values, without spending much time in coding. I am not saying this is the best way to explore but still this is one kind of way to do coding
anandprems/sai_ram_engineering_machine_learning
anandprems/Tree_Based_Machine_learning_PTB_dataset_
The primary objective of this particular paper is to classify the health-related data without feature extraction in Machine Learning, which hinder the performance and reliability. The assumption of our work will be like, can we able to get better result for health-related data with the help of Tree based Machine Learning algorithms without extracting features like in Deep Learning. This study performs better classification with Tree based Machine Learning approach for the health-related medical data. After doing pre-processing, without feature extraction, i.e., from raw data signal with the help of Machine Learning algorithms we are able to get better results. The presented paper which has better result even when compared to some of the advanced Deep Learning architecture models. The results demonstrate that overall classification accuracy of Random Forest, XGBoost, LightGBM and CatBoost, Tree-based Machine Learning algorithms for normal and abnormal condition of the datasets was found to be 97.88%, 98.23%, 98.03% and 95.57% respectively.
anandprems/workshop-related-to-ML-and-DL-
M.O.P. Vaishnav College for Women - 2 days workshop
anandprems/YouTube-Video-Processing-Scripts