AI & ML- Python

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About:

Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.Machine learning(ML) is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.

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Number of Hours
36 hours
 
Live/Recorded
36 hours


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Projects

Sl.No Project Title Key Skills
1 Prediction of Diabetes RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier, ExtraTreesClassifier
2 To correctly classify tweets from the datatset as either as positive or negative Naive Bayes, KNN, Logistic Regression, Decision Tree
3 To identify ships in a satellite image Convolutional Neural Network
4 Classify whether the person has the heart disease or not Support Vector Classifier, Logistic Regression
5 Predict the Loan Approval GradientBoostingClassifier, Logistic Regression, KNeighborsClassifier, RandomForestClassifier
6 Predict the credit card approval DecisionTreeClassifier, KNeighborsClassifier, GaussianNB
7 Bank Marketing Campaign Predictive Analysis LinearDiscriminantAnalysis, AdaBoostClassifier, KNeighborsClassifier
8 To classify whether the personhas pneumonia from X-Ray reeports Convolutional Neural Network
9 To predict the outcome of the king-rook vs. king endgame LogisticRegression, Support Vector Classifier
10 To predict the person is infected by malaria or not by visualizing the cell image of a person ANN, CNN
11 Predicting the bik-buyers SVM, DT
12 Classfication of cars LogisticRegression, Support Vector Classifier, KNN
13 Evaluation of Nursery School Applications RandomForestClassifier, KNeighborsClassifier
14 Predict the outcome of the chess game Support Vector Machine, Random Forest Classifier
15 Predict the critical temperature of a super conductor RandomForestRegressor, XGBRegressor
16 Predict heart disease occurance GaussianNB
17 Identify ships from Space Bourne Photography CNN
18 Distracted Driver Detection Convolutional Neural Network
19 Evaluate the car based on the intermediate concepts Logistic Regression, K-Neighbors Classifier
20 Predict the appliance energy usage using sensor reading and weather data Ridge Regression, Lasso Regresssion, Extra Trees
21 Identfing wether the people is suffuring from lever disease or not (Classification) RandomForestClassifier
22 To detect forged notes based on the data set of forged and genunine bank_note_Specimens RandomForestClassifier
23 To predict the energy consuption by home appliances LinearRegression
24 To increase the effectiveness of their Employees GaussianMixture,LogisticRegression, clusters,RandomForestClassifier
25 To predict the Sustainability of hand pump LogisticRegression,MLPClassifier,RandomForestClassifier
26 to predict the mobile price based on its Quailities and features DecisionTreeClassifier,LinearRegression
27 to classify plant_seeding LabelBinarizer,Dense, Dropout, Flatten, Conv2D, MaxPool2D, GlobalMaxPoolin, ImageDataGenerator,Sequential,ReduceLROnPlateau
28 to predicting the burned area due to small fires based on the data set neural_network, linear_model, preprocessing, svm, tree,RandomForestRegressor, RandomForestClassifier,KFold,GaussianNB
29 to predicting the burned area due to small fires based on the data set neural_network, linear_model, preprocessing, svm, tree,RandomForestRegressor, RandomForestClassifier,KFold,GaussianNB
30 The Aim of the project to identify whether the driver is distracted or not while driving the car CNN (Classification)
31 Feature popularity of news article prior to its publication Logistic regression
32 predecting the price of the car based on car features lLogistic regression
33 This project is to explore the results of applying machine learning techniques to SMS spam detection. Decisition Tree classification
34 Air Quality prediction model using machine learning algorithm Linear regression,support vector regression
35 Feature popularity of news article prior to its publication estimating the no. shares,likes,comments etc.. Random forest classification
36 Drowsiness detection System Neural Networks, OpenCV
37 Gender Detection and Age Prediction OpenCV, Convolutional Neural Networks
38 Hand-written digit recognition Artificial Neural Networks,CNN
39 Classify the images into dog or cat based on the features of the images. Convolutional Neural Network