kumar-gourabh Goto Github PK

analyzing-movie-dataset

Analyzing movie dataset using Python Fundamentals

analyzing-weather-dataset

Analyzing weather dataset using Numpy & Pandas

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

basic_projects

These are a few basic Projects that every Data Science / ML Enthusiast should be aware. These contain some of my first attempts at some famous datasets like the Titanic Dataset etc. It's recommended for beginners.

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

dsdata

Data Science ML

evaluative_projects_ml

As part of my Evaluative Projects, these are some exciting and good projects that I am doing to learn by practicing

fliprobo

Assignments and Projects done while doing my 6 month internship with Flip Robo

greyatom-python-for-data-science

A collection of projects as part of the Python for Data Science program at GreyAtom EduTech Pvt Ltd

iitm-ipl-21-powerplay-scores-prediction

Took Part in a Hackathon by IIT Madras. Goal was to predict the scores after 6 overs of each upcoming match

image-extraction-and-classification

Images are one of the major sources of data in the field of data science and AI. This field is making appropriate use of information that can be gathered through images by examining its features and details. We are trying to give you an exposure of how an end to end project is developed in this field. The idea behind this project is to build a deep learning-based Image Classification model on images that will be scraped from e-commerce portal. This is done to make the model more and more robust. This task is divided into two phases: Data Collection and Model Building. Data Collection Phase: In this section, you need to scrape images from e-commerce portal, Amazon.com. The clothing categories used for scraping will be: Sarees (women) Trousers (men) Jeans (men) You need to scrape images of these 3 categories and build your data from it. That data will be provided as an input to your deep learning problem. You need to scrape minimum 200 images of each categories. There is no maximum limit to the data collection. You are free to apply image augmentation techniques to increase the size of your data but make sure the quality of data is not compromised. Remember, in case of deep learning models, the data needs to be big for building a good performing model. More the data, better the results. Model Building Phase: After the data collection and preparation is done, you need to build an image classification model that will classify between these 3 categories mentioned above. You can play around with optimizers and learning rates for improving your model’s performance.

learndatascience

Open Content for self-directed learning in data science

marketing-campaign

Predict if the client will subscribe to a term deposit based on the analysis of the marketing campaigns the bank performed.

marketplace-feature-jobathon

Data Engineering Competition Conducted by Analytics Vidhya with 6000+ Registered Participants. I secured a rank of 121 with this code, needs some improvements.

nlp

olympics-data-analysis

Olympics Data Analysis

recent-projects

test

This is test

visualizing-the-weather-data-set

Visualizing the Weather Dataset using Matplotlib