saarahasad Goto Github PK

ai-legal-project

all-things-qaraa

angular-5-basic-grid-view

Grid view using Angular 5

annotation-tool-spa

Annotation tool using Angular 6, Firebase - Cloud Firestore

arabiyah-classes-android-application

It is an android application developed using Java. It's features include: 1. Provides information about the institute and courses. 2. Allows users to enrol and purchase courses.

bears-pandas-classification-using-fast.ai

bitcointracker-ios-app

Tracks the price of Bitcoin

brooklyn-nine-nine-playlist-ios-app

Hilarious Brooklyn Nine-Nine playlist

chapter-1-machinelearning-basic-data-preprocessing

The basic data preprocessing steps before you start off with your ML algorithm.

chapter-10-ml-ad-market-analyzer-support-vector-machine

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

chapter-11-ml-ad-market-analyzer-kernel-svm

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

chapter-12-ml-ad-market-analyzer-decision-tree-classification

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

chapter-12-ml-ad-market-analyzer-naive-bayes

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

chapter-13-ml-ad-market-analyzer-random-forest-classification

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

chapter-14-mall-target-customer-group-identification-using-kmeans-clustering

A mall has hired you as a machine learning scientist to segment their clients into different groups based on these two metrics: the annual income and the spending score. How do you do it?

chapter-15-mall-target-customer-group-identification-using-hierarchical-clustering

A mall has hired you as a machine learning scientist to segment their clients into different groups based on these two metrics: the annual income and the spending score. How do you do it?

chapter-16-optimising-sales-using-apriori

Apriori algorithm within Association Rule Learning helps the manager of a store to layout how items are placed in the store. It tells us if constumers bought this product, then they are likely to buy this other product. Thus, we could place these products together and customers are more like to buy both products.

chapter-17-sentiment-analysis-of-restaurant-review-using-naive-bayes

Predicting the sentiment(Positive or Negative) of restaurant reviews.

chapter-18-sentiment-analysis-of-restaurant-review-using-a-svm

Predicting the sentiment(Positive or Negative) of restaurant reviews.

chapter-19-sentiment-analysis-of-restaurant-review-using-random-forest-classification

Predicting the sentiment(Positive or Negative) of restaurant reviews.

chapter-2-machinelearning-simple-linear-regression

A Simple Linear Regression Model implemented using sklearn.linear_model.LinearRegression in Python

chapter-3-machinelearning-multiple-linear-regression-with-backward-elimination

Multiple linear regression is to assess if a continuous dependent variable can be predicted from a set of independent variables. The model is built using 1 of the 5 possible approaches - Backward Elimination (fastest method)

chapter-4-ml-identifying-a-salary-bluffer-using-polynomial-regression

If you have a company, check if the new employee coming in demanding $X as salary is bluffing or telling the truth on how much he should receive based on previous stats using a polynomial regression model.

chapter-5-ml-identifying-a-salary-bluffer-using-support-vector-regression

If you have a company, check if the new employee coming in demanding $X as salary is bluffing or telling the truth on how much he should receive based on previous stats using a support vector regression model.

chapter-6-ml-identifying-a-salary-bluffer-using-decision-tree-regression

If you have a company, check if the new employee coming in demanding $X as salary is bluffing or telling the truth on how much he should receive based on previous stats using a decision tree regression model.

chapter-7-ml-identifying-a-salary-bluffer-using-random-forest-regression

If you have a company, check if the new employee coming in demanding $X as salary is bluffing or telling the truth on how much he should receive based on previous stats using a random forest regression model.

chapter-8-ml-ad-market-analyser-logistic-regression

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

chapter-9-ml-ad-market-analyzer-k-nearest-neighbors

A social network stores user data including their age and estimated salary. It has ads running on its platforms. It collects data such as the user clicks on advertisements and purchases made from them. Given an ad for a car company, it would predict if the user would purchase the car based on his/her age and estimated salary.

cloudwork-exercise

Take home task for the frontend application engineer role

course-v3

The 3rd edition of course.fast.ai