MoinDalvs

Time_Series_Forecasting_From_Scratch

Gradient_Boosting_Algorithms_From_Scratch

4 Boosting Algorithms You Should Know – GBM, XGBoost, LightGBM & CatBoost

Forecasting_Airline_Passengers_Traffic

Forecast the Airlines Passengers. Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for Forecasting.

Assignment_Web_Scraping_Emotion_Mining

Extract reviews of any product from ecommerce website like amazon

Neural_Networks_Forest_Fire_Classification

PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS

Neural_Networks_From_Scratch

Neural_Networks_From_Scratch

Neural_Network_Regression_Gas_Turbines

Predicting Turbine Energy Yield (TEY) using ambient variables as features.

Assignment_Decision_Tree_1

Assignment_KNN_Glass

Problem Statement Implement a KNN model to classify the different types of Glass

Assignment_Random_Forest_1

Use Random Forest to prepare a model on fraud data treating those who have taxable income <= 30000 as "Risky" and others are "Good"

Gradient_Descent_For_beginners

Gradient_descent_Complete_In_Depth_for beginners

Assignment_Decision_Tree_2

Assignment_Random_Forest_2

A cloth manufacturing company is interested to know about the segment or attributes causes high sale. Approach - A Random Forest can be built with target variable Sale (we will first convert it in categorical variable) & all other variable will be independent in the analysis.

Assignment_SVM_Forest_Fire_Prediction

Assignment_SVM_Salary_Dataset

Data_Analyst_Assignment

#Excelr_Assignment

Forecasting_CocaCola_prices.

Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for Forecasting.

K-Nearest_Neigbor_KNN

KNN (K_Nearest_Neighbor)

Survival_Analysis_From_Scratch

An introduction to the concepts of Survival Analysis and its implementation in lifelines package for Python.

SVM_Hyperparameter_Tuning_Kernel_Tricks

Effect of Gamma values and C values visualization on dataset and errors/misclassification

Assignment_Naive_Bayes_Salary_dataset

Problem Statement Prepare a classification model using Naive Bayes for salary data

Decision_tree_CART

Different_types_Linear_Regressions

Logistic_Regression_Claimants

Overview¶ CASENUM- Case number to identify the claim, a numeric vector ATTORNEY Whether the claimant is represented by an attorney (=1 if yes and =2 if no) CLMSEX Claimant’s gender (=1 if male and =2 if female), a numeric vector CLMINSUR Whether or not the driver of the claimant’s vehicle was uninsured (=1 if yes, =2 if no) SEATBELT Whether or not the claimant was wearing a seatbelt/child restraint (=1 if yes, =2 if no) CLMAGE Claimant’s age, a numeric vector LOSS The claimant’s total economic loss (in thousands)

Multi_class_Classification_Iris

Multiple Class Iris Dataset Classification Model

Naive_Bayes_Multinomial_Gaussian_Bernoulli

Sentiment_Analysis_on_-Elon_musk_Tweets

Perform sentimental analysis on the Elon-musk tweets (Elon-musk.csv)

SQL_Basic-Queries_

MySQL

Text_Mining_NLP

Natural Language Processing

Convolution_Neural_Network_For_Beginners