A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

A New, Interactive Approach to Learning Python

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

Karma of Humans is AI

An anytime implementation of scikit-learn GridSearchCV

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

Creating Predictions for Numerai with Keras and scikit-learn

In this project, I employ several supervised algorithms to accurately predict an individual income using data collected from the 1994 U.S. Census. We implement various testing procecures to choose the best candidate algorithm from preliminary results and further optimize this algorithm to best model the data.

Learn and Explore

Hyperparameters-Optimization

Classify pictures by architectural style and recognize objects with CNNs and YOLO

Sentiment Analysis of Tweets related to Vaccine.

Digit recognition using SVM

Prediction of bike rental count hourly or daily based on the environmental and seasonal settings using data set from two-years historical log corresponding to years 2011 and 2012 from Capital Bikeshare system, Washington D.C., USA

I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

A case study on predicting customer churn using machine learning.

PREDICT TUMOR IS MALIGNANT OR BENIGN

Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)

Capstone Project Gold Price Prediction using Machine learning Approach for Udacity Machine Learning engineer Nanodegree Program

Fake News Detection System for detecting whether news is fake or not. The model is trained using "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection. Link for dataset: https://arxiv.org/abs/1705.00648.

Build a classifier to classsification transport using sift and svm

It is an attempt to bring along various techniques in machine learning and deep learning

Machine Learning. I am building a prediction model, using Logistic Regression, and evaluating its performance with confusion matrix, GridsearchCV,

Boston Housing Price prediction and comparison of evaluation metrics by using Decision tree regressor algorithm and tuning parameters by using GridSearchCV (with different parameters like Criterion, Max depth, min samples split and min samples leaf ...)

Bank customers churn dashboard with predictions from several machine learning models.

This project is to classify breast cancer using SVM-Classifier and further improving the model using GridSearch

Walmart Sales Forecast Solution

Hyperparameter tuning using Sklearn Pipelines

Hyperparameter Tuning done on Random Forest Classifier using Hyperopt over Pima Diabetes Dataset!!