Itachi Uchiha's Projects
To maintain a streak by completing a project per day , we'll focus to complete project everyday
Email Newsletter
To main streak & stay motivated commit a project daily related to computer vision and open cv
GitHub Profile Page
Config files for my GitHub profile. You can simply copy it and paste it in our README file make changes as per your skills and also change alanbinu007 to your username
Amazon SageMaker examples for prebuilt framework mode containers, a.k.a. Script Mode, and more (BYO containers and models etc.)
Used Machine learning to predict the price of a car based on several characteristics. The objective is to build a model to understand the factors that drive the car of the price. This will help the automobile company launch their new car in the market effectively by pricing it better. Tasks performed : - Performed EDA on the data - Performed data cleanup as required - Picked the best variable for making a simple linear regression model - Perform train test split - Build model using best variable and report the R2 - Prepared a multiple regression model >> Applied feature selection approaches such as Variance Inflation Factor(VIF) , Ordinary Least Squares (OLS) and Recursive Feature elimination(RFE). - Final model is formed in a interpretable form
Analyzed the bank data , formed visualizations using seaborn , Built a model based on selected features which we got from OLS , RFE and VIF . And made predictions using Logistic and random forest algorithms.
Boston data with LINEAR REGRESSION
Conv Layers using Filters ,Strides , padding , and Max pooling layers. Transfer Learning , Style Transfers , Auto Encoders , Dog breed classification , MNIST , CIFAR 10 Augmentation and Flower type Classification
Quiz & Assignment of Coursera
Done EDA for India as well as for World using the data which we have collected through API's
This very basic script can be used to automate some steps on Co-WIN Platform.
Projects from Basic to advanced using neural networks ( CNN, RNN ) Which can be based on math using numpy or else u sing deep learning algorithms i.e. neural networks
Data structures, Algorithms & Dynamic Programming
Data Visualizations
Digits images generation , Pix 2 Pix , Cycle-GAN,SVH numbers generation and New faces Generation using Linear hidden layers, Deep CGANS , and using Batch normalization to perform better in Generator and Discriminators.
This includes projects of Supervised : such as Regression - SLR , MLR ,Classification - SVM , Log Reg , Dec Tree , KNN and Unsupervised : K Means , Heirarchical & DBSCAN & aslo recommendor systems
Matlab assignments and projects
Algorithms developed from scratch by de-bunking black box of ML-Algorithms