Pinned Repositories
10-steps-to-become-a-data-scientist
📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.
anomaly_detection
This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.
argo-workflows
Workflow engine for Kubernetes
awesome-ml-for-cybersecurity
:octocat: Machine Learning for Cyber Security
CKA-K8S
data-science-complete-tutorial
Notebooks to learn data science - Videos https://www.edyoda.com/course/1416
Deep-Learning-For-Hackers
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis)
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Deploy-machine-learning-model
Dockerize and deploy machine learning model as REST API using Flask
Time-series-analysis-using-Python
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data.
vikram687's Repositories
vikram687/feature-selector
Feature selector is a tool for dimensionality reduction of machine learning datasets
vikram687/competitive-data-science
Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course
vikram687/text-analytics-with-python
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
vikram687/mlflow-titanic
A quick demo to show how MLflow works using the Titanic dataset.
vikram687/movielens
4 different recommendation engines for the MovieLens dataset.
vikram687/Time-Series-Forecasting
Forecasting Monthly Sales of French Champagne - Perrin Freres
vikram687/text-analytics-w-python-2e
Source Code for 'Text Analytics with Python,' 2nd Edition by Dipanjan Sarkar
vikram687/MLResources
Repository for Machine Learning resources, frameworks, and projects. Managed by the DLSU Machine Learning Group.
vikram687/Telecom_Churn_Model
Analyse customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn and identify the main indicators of churn.
vikram687/Kaggle-Survey-Salary-Prediction
This is a data science project that uses survey responses from the 2018 Kaggle survey to train various machine learning models (linear regression, knn, gradient boosting, random forest) to make predictions on a respondent's Salary.
vikram687/10-steps-to-become-a-data-scientist
📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.
vikram687/practical-machine-learning-with-python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
vikram687/data-science-complete-tutorial
Notebooks to learn data science - Videos https://www.edyoda.com/course/1416
vikram687/RNN-Time-series-Anomaly-Detection
RNN based Time-series Anomaly detector model implemented in Pytorch.
vikram687/Multivariate-time-series-models-in-Keras
This repository contains a throughout explanation on how to create different deep learning models in Keras for multivariate (tabular) time series prediction.
vikram687/Deep-Learning-with-Keras
Code repository for Deep Learning with Keras published by Packt
vikram687/anomaly_detection
This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.
vikram687/githu-demo
Simple Demo
vikram687/Hello2
vikram687/Hello-
vikram687/Sentiment-Analysis-Twitter
:mortar_board:RESEARCH [NLP :thought_balloon:] We use different feature sets and machine learning classifiers to determine the best combination for sentiment analysis of twitter.
vikram687/Hands-On-Recommendation-Systems-with-Python
Hands-On Recommendation Systems with Python published by Packt
vikram687/deep-learning-for-natural-language-processing
Source Code for 'Deep Learning for Natural Language Processing' by Palash Goyal, Sumit Pandey and Karan Jain
vikram687/AutoEncoders-for-Anomaly-Detection
vikram687/predict-nps
Machine Learning algorithm to predict NPS scores from user feedback.
vikram687/Customer_segmentation
Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.
vikram687/TwitterUSAirlineSentiment
Code to experiment with text mining techniques for sentiment analysis in data set is from Kaggle.
vikram687/Practical-Time-Series-Analysis
Practical Time-Series Analysis, published by Packt
vikram687/KerasQuantileModel
Quantile Regression using Deep Learning. An alternative to Bayesian models to get uncertainty.
vikram687/pyspark-tutorials
Code snippets and tutorials for working with social science data in PySpark