Mrinal Walia's repositories
Python-for-Data-Science-and-Machine-Learning-Bootcamp
program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning: Programming with Python NumPy with Python Using pandas Data Frames to solve complex tasks Use pandas to handle Excel Files Web scraping with python Connect Python to SQL Use matplotlib and seaborn for data visualizations Use plotly for interactive visualizations Machine Learning with SciKit Learn, including: Linear Regression K Nearest Neighbors K Means Clustering Decision Trees Random Forests Natural Language Processing Neural Nets and Deep Learning Support Vector Machines and much, much more!
Deep-Learning-with-OpenCV
Deep Learning is a fast growing domain of Machine Learning and if you’re working in the field of computer vision/image processing already (or getting up to speed), it’s a crucial area to explore. With OpenCV 3.3, we can utilize pre-trained networks with popular deep learning frameworks. The fact that they are pre-trained implies that we don’t need to spend many hours training the network — rather we can complete a forward pass and utilize the output to make a decision within our application. OpenCV does not (and does not intend to be) to be a tool for training networks — there are already great frameworks available for that purpose. Since a network (such as a CNN) can be used as a classifier, it makes logical sense that OpenCV has a Deep Learning module that we can leverage easily within the OpenCV ecosystem. Popular network architectures compatible with OpenCV 3.3 include: GoogleLeNet (used in this blog post) AlexNet SqueezeNet VGGNet (and associated flavors) ResNet
Data-Structures-And-Algorithm-Practice-Programs
While studying dsa , all my practice programs are being commited to github for my personal use !!! XD
Portfolio-Website-Django
This is my Personal Portfolio website In Django
Access-Phone-camera-for-OpenCV
If you are having problem is using your laptop webcam or you dont have a good webcam for working with OpenCV or related Computer vision projects then, Nothing to worry about because using this project source code and following the readme instructions you can use your phone came to work with OpenCV library in Python.
android-vision
Sample code for the Android Mobile Vision API.
BodyPoseEstimationAndroid
🙋♂️Use Body Pose Estimation to perform pose matching on Android
CALTECH-101-Dataset-
The CALTECH-101 dataset is a dataset of 101 object categories with 40 to 800 images per class. Most images have approximately 50 images per class.
Cam-Scanner-in-python
The script takes an image as input and then scans the document from the image by applying few image processing techniques and gives the output image with scanned effect
cloud-scanner
Cloud Scanner is a cloud agnostic tool that extracts cloud based resources from cloud providers like Azure and ingests them into a configured data source for further processing.
Creating-GIFs-with-OpenCV
In this project you can learn how to create animated GIFs using OpenCV, Python, and ImageMagick.
Credit-Card-Fraud-Detection
Context It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Content The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions. It contains only numerical input variables which are the result of a PCA transformation. Unfortunately, due to confidentiality issues, we cannot provide the original features and more background information about the data. Features V1, V2, ... V28 are the principal components obtained with PCA, the only features which have not been transformed with PCA are 'Time' and 'Amount'. Feature 'Time' contains the seconds elapsed between each transaction and the first transaction in the dataset. The feature 'Amount' is the transaction Amount, this feature can be used for example-dependant cost-senstive learning. Feature 'Class' is the response variable and it takes value 1 in case of fraud and 0 otherwise.
data-science-from-scratch
code for Data Science From Scratch book
Deep-Learning-basics-with-Python-TensorFlow-and-Keras
Deep Learning basics with Python, TensorFlow and Keras(SENTDEX TUTORIALS)
deepjazz
Deep learning driven jazz generation using Keras & Theano!
flutter
Flutter makes it easy and fast to build beautiful mobile apps.
flutter_architecture_samples
TodoMVC for Flutter
ignite
High-level library to help with training neural networks in PyTorch
image-classification
Binary image classification tensorflow demo
microservices-demo
Sample cloud-native application with 10 microservices showcasing Kubernetes, Istio, gRPC and OpenCensus. Provided for illustration and demo purposes.
mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
opencv_contrib
Repository for OpenCV's extra modules
real-time-face-recognition
A face-recognition project with webcam, web-sockets and python
scikit-learn
scikit-learn: machine learning in Python
turicreate
Turi Create simplifies the development of custom machine learning models.