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This document describes a project to predict mental fitness using machine learning regression models. The project will use parameters like schizophrenia, bipolar disorder, anxiety, depression, drug usage, and alcohol usage to predict an individual's mental fitness score. A random forest regressor is used as the machine learning model. The model is trained on datasets from online sources. Evaluation metrics like mean squared error indicate the model performs well. Potential end users are medical centers and researchers. The project was implemented from scratch using Python libraries like Pandas, Scikit-Learn, and Seaborn.
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The slides were used in a trial session for a student aiming to learn python to do Data science projects .
The session video can be watched from the link below
https://youtu.be/CwCe1pKOVI8
I have over 20 years of experience in both teaching & in completing computer science projects with certificates from Stanford, Alberta, Pennsylvania, California Irvine universities.
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Unit 2-ML.pptx
The document provides an introduction to supervised learning. It discusses how supervised learning models are trained on labelled datasets containing both input data and corresponding results or labels. The model learns from these examples to predict accurate results for new, unseen data. Common applications of supervised learning mentioned include sentiment analysis, recommendations, and spam filtration. Decision trees and K-nearest neighbors are discussed as examples of supervised learning algorithms. Decision trees use a top-down approach to split the dataset into more homogeneous subsets. K-nearest neighbors classifies new data based on similarity to labelled examples in the training set.
heart final last sem.pptx
This document proposes using machine learning algorithms to predict heart disease at early stages. It discusses problems with current diagnosis methods and the need for an automated system. The proposed system would use a dataset of 779 individuals and various machine learning algorithms to predict the likelihood of heart disease for new individuals. It describes preprocessing the data, training models like logistic regression, random forest, SVM and comparing their performance. The system architecture involves preprocessing, training models, testing them and predicting heart disease risk. Modules like SVM, decision trees, random forest and naive Bayes are explained. The document concludes by discussing implementation and outputs like algorithm accuracies for training and test sets.
Industrial training ppt
Hrjeet Singh completed a 42-day online industrial training from Internshala located in Gurgaon, India. During the training, Singh learned about machine learning concepts including classification, regression, linear regression, logistic regression, decision trees, and K-means clustering. Singh also completed a project using machine learning classifiers to detect breast cancer by analyzing features of breast cancer patient and normal cells.
House price prediction
The ppt is all about project description of the creation of a machine learning model for house price prediction in an Indian city Bengaluru.
Introductionedited
This document discusses random forest machine learning algorithms and their use in predictive modeling. It provides context on random forests, including that they perform well for both classification and regression tasks, are less prone to overfitting than decision trees, and provide good predictive accuracy while also being interpretable. The document then discusses preprocessing methods like stemming, removing punctuation and stop words that can be applied before using natural language processing algorithms. It highlights the advantages of random forests, such as their ability to handle different data types, parallelizability, and stability. It also notes limitations like lack of interpretability for some users and potential for overfitting on some data sets.
Data science notes for ASDS calicut 2.pptx
Data science involves both statistics and practical hacking skills. It is the engineering of data - applying tools and theoretical understanding to data in a practical way. Statistical modeling is the process of using mathematical models to analyze and understand data in order to make general predictions. There are several statistical modeling techniques including linear regression, classification, resampling, non-linear models, tree-based methods, and neural networks. Unsupervised learning identifies patterns in data without pre-existing categories by techniques like clustering. Time series forecasting predicts future values based on patterns in historical time series data.
Machine Learning_Unit 2_Full.ppt.pdf
This document provides an overview of machine learning concepts and techniques. It discusses supervised learning methods like classification and regression using algorithms such as naive Bayes, K-nearest neighbors, logistic regression, support vector machines, decision trees, and random forests. Unsupervised learning techniques like clustering and association are also covered. The document contrasts traditional programming with machine learning and describes typical machine learning processes like training, validation, testing, and parameter tuning. Common applications and examples of machine learning are also summarized.
software engineering powerpoint presentation foe everyone
This document describes a student grade prediction system called StudGrad developed by four students. It uses a linear regression machine learning model to predict student grades based on factors like study hours, attendance, previous grades, and extracurricular activities. The document outlines the data collection, model training, evaluation, and deployment process. It also discusses using an Agile software development process and performs a feasibility analysis and SWOT analysis of the project.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
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Statistical Learning and Model Selection (1).pptx
This document discusses statistical learning and model selection. It introduces statistical learning problems, statistical models, the need for statistical modeling, and issues around evaluating models. Key points include: statistical learning involves using data to build a predictive model; a good model balances bias and variance to minimize prediction error; cross-validation is described as the ideal procedure for evaluating models without overfitting to the test data.
LOAN APPROVAL PRDICTION SYSTEM USING MACHINE LEARNING.
This document describes a machine learning model for predicting loan approvals. It discusses collecting loan application data and preprocessing the data which includes cleaning, feature selection, and scaling. Various machine learning algorithms are trained on the data including logistic regression, decision trees, random forest, support vector machines, and gradient boosting. Their accuracies are compared and random forest is found to perform best. The optimal model is deployed with a user interface created using Streamlit. The system aims to automate and improve the loan approval process for banks.
IRJET- Survey on Face Recognition using Biometrics
This document describes a survey on face recognition using biometrics. It discusses using the Haar cascade algorithm with OpenCV in Python to detect faces in images and video. The algorithm involves selecting Haar features, creating integral images for rapid calculation of features, training classifiers with AdaBoost, and cascading the classifiers. It trains on positive and negative image datasets to detect faces and then recognizes faces by extracting principal components and comparing to trained data. The system fulfills basic face detection and recognition needs at low cost for applications like security and real-time analysis. Improving the algorithm involves adding more training images to increase accuracy.
It's Machine Learning Basics -- For You!
Machine learning is a branch of artificial intelligence that uses data and algorithms to enable computers to learn and improve at tasks without being explicitly programmed. There are three main types of machine learning: supervised learning which uses labeled training data, unsupervised learning which finds patterns in unlabeled data, and reinforcement learning where an agent learns from trial-and-error interactions with an environment. Machine learning is important because it allows automation through data-driven pattern recognition, enables personalization at scale, and accelerates scientific discovery through analysis of massive and complex datasets.
MACHINE LEARNING LIFE CYCLE
The document outlines the 7 key steps of a machine learning life cycle: 1) Gathering data from various sources, 2) Preparing the data through exploration and preprocessing, 3) Cleaning and formatting the data through wrangling, 4) Analyzing the data using models and techniques, 5) Training models using machine learning algorithms, 6) Testing the trained models on new data, and 7) Deploying accurate models into real systems if testing performance is satisfactory. The goal of the life cycle is to find a solution to a problem by developing and evaluating machine learning models through these iterative steps.
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Data Science & AI Road Map by Python & Computer science tutor in Malaysia
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software engineering powerpoint presentation foe everyone
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Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
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LOAN APPROVAL PRDICTION SYSTEM USING MACHINE LEARNING.
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AadiShakti Projects ( Asp Cranes ) Raipur
Welcome to ASP Cranes, your trusted partner for crane solutions in Raipur, Chhattisgarh! With years of experience and a commitment to excellence, we offer a comprehensive range of crane services tailored to meet your lifting and material handling needs.
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Digital Fleet Management - Why Your Business Need It?
Fleet management these days is next to impossible without connected vehicle solutions. Why? Well, fleet trackers and accompanying connected vehicle management solutions tend to offer quite a few hard-to-ignore benefits to fleet managers and businesses alike. Let’s check them out!
EV Charging at Multifamily Properties by Kevin Donnelly
Kevin Donnelly gave this presentation at the Forth Addressing The Challenges of Charging at Multi-Family Housing webinar on June 11, 2024.
一比一原版(Columbia文凭证书)哥伦比亚大学毕业证如何办理
一模一样【微信：176555708】【(Columbia文凭证书)哥伦比亚大学毕业证成绩单Offer】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
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留信网认证的作用:
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4:这个认证书并且可以归档倒地方
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我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
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What do the symbols on vehicle dashboard mean?
Ever been troubled by the blinking sign and didn’t know what to do?
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多年留学服务公司,拥有海外样板无数能完美1:1还原海外各国大学degreeDiplomaTranscripts等毕业材料。海外大学毕业材料都有哪些工艺呢？工艺难度主要由：烫金.钢印.底纹.水印.防伪光标.热敏防伪等等组成。而且我们每天都在更新海外文凭的样板以求所有同学都能享受到完美的品质服务。
国外毕业证学位证成绩单办理方法：
1客户提供办理奥克兰理工大学奥克兰理工大学毕业证成绩单信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
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— — — — 我们是挂科和未毕业同学们的福音我们是实体公司精益求精的工艺！ — — — -
一真实留信认证的作用(私企外企荣誉的见证):
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4：个人职称评审加20分个人信誉贷款加10分。
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一比一原版(WashU文凭证书)圣路易斯华盛顿大学毕业证如何办理
一模一样【微信：176555708】【(WashU文凭证书)圣路易斯华盛顿大学毕业证成绩单Offer】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Hand Gesture Control Robotic Arm using image processing.pptx
Hand Gesture Control Robotic Arm using image processing
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一比一原版(UNITEC毕业证)UNITEC理工学院毕业证成绩单如何办理
UNITEC毕业证【微信95270640】☀《UNITEC理工学院毕业证购买》Q微信95270640《UNITEC毕业证模板办理》文凭、本科、硕士、研究生学历都可以做,《文凭UNITEC毕业证书原版制作UNITEC成绩单》《仿制UNITEC毕业证成绩单UNITEC理工学院学位证书pdf电子图》毕业证
全套服务：UNITEC理工学院UNITEC理工学院硕士毕业证成绩单真实回国人员证明 #真实教育部认证。让您回国发展信心十足#铸就十年品质！信誉！实体公司！可以视频看办公环境样板如需办理真实可查可以先到公司面谈勿轻信小中介黑作坊！
可以提供UNITEC理工学院钢印 #水印 #烫金 #激光防伪 #凹凸版 #最新版的毕业证 #百分之百让您绝对满意
印刷DHL快递毕业证 #成绩单7个工作日真实大使馆教育部认证1个月。为了达到高水准高效率
请您先以qq或微信的方式对我们的服务进行了解后如果有UNITEC理工学院UNITEC理工学院硕士毕业证成绩单帮助再进行电话咨询。
国外毕业证学位证成绩单如何办理：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作UNITEC理工学院毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。嘿嘿的笑连连说记得记得但别忘了拿奖状进城啊考试一结束山娃就迫不及待地给父亲挂电话：爸我拿奖了三好学生接我进城吧父亲果然没有食言第二天就请假回家接山娃离开爷爷奶奶的那一刻山娃又伤心得泪如雨下宛如军人奔赴前线般难舍和悲壮卧空调大巴挤长蛇列车山娃发现车上挤满了叽叽喳喳的同龄人皆一脸惊喜地四处瞅山娃不认识他们也无暇去套近乎一味地跟着父亲昼夜兼程第二天凌晨就辗转到了父亲的城哇父亲的城真的好大好美哟走出广州有
原版制作(Exeter毕业证书)埃克塞特大学毕业证完成信一模一样
学校原件一模一样【微信：741003700 】《(Exeter毕业证书)埃克塞特大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Case Study on Failure Product - Tata Nano
This is a detailed case study of Failure Product ( Tata Nano ).
快速办理(napier毕业证书)英国龙比亚大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(napier毕业证书)英国龙比亚大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(OP毕业证)奥塔哥理工学院毕业证成绩单如何办理
OP毕业证【微信95270640】《如何办理奥塔哥理工学院毕业证认证》【办证Q微信95270640】《奥塔哥理工学院文凭毕业证制作》《OP学历学位证书哪里买》办理奥塔哥理工学院学位证书扫描件、办理奥塔哥理工学院雅思证书！
国际留学归国服务中心《如何办奥塔哥理工学院毕业证认证》《OP学位证书扫描件哪里买》实体公司，注册经营，行业标杆，精益求精！
如果您是以下情况，我们都能竭诚为您解决实际问题：【公司采用定金+余款的付款流程，以最大化保障您的利益，让您放心无忧】
1、在校期间，因各种原因未能顺利毕业，拿不到官方毕业证+微信95270640
2、面对父母的压力，希望尽快拿到奥塔哥理工学院奥塔哥理工学院毕业证学位证；
3、不清楚流程以及材料该如何准备奥塔哥理工学院奥塔哥理工学院毕业证学位证；
4、回国时间很长，忘记办理；
5、回国马上就要找工作，办给用人单位看；
6、企事业单位必须要求办理的；
面向美国乔治城大学毕业留学生提供以下服务:
【★奥塔哥理工学院奥塔哥理工学院毕业证学位证毕业证、成绩单等全套材料，从防伪到印刷，从水印到钢印烫金，与学校100%相同】
【★真实使馆认证（留学人员回国证明），使馆存档可通过大使馆查询确认】
【★真实教育部认证，教育部存档，教育部留服网站可查】
【★真实留信认证，留信网入库存档，可查奥塔哥理工学院奥塔哥理工学院毕业证学位证】
我们从事工作十余年的有着丰富经验的业务顾问，熟悉海外各国大学的学制及教育体系，并且以挂科生解决毕业材料不全问题为基础，为客户量身定制1对1方案，未能毕业的回国留学生成功搭建回国顺利发展所需的桥梁。我们一直努力以高品质的教育为起点，以诚信、专业、高效、创新作为一切的行动宗旨，始终把“诚信为主、质量为本、客户第一”作为我们全部工作的出发点和归宿点。同时为海内外留学生提供大学毕业证购买、补办成绩单及各类分数修改等服务；归国认证方面，提供《留信网入库》申请、《国外学历学位认证》申请以及真实学籍办理等服务，帮助众多莘莘学子实现了一个又一个梦想。
专业服务，请勿犹豫联系我
如果您真实毕业回国，对于学历认证无从下手，请联系我，我们免费帮您递交
诚招代理：本公司诚聘当地代理人员，如果你有业余时间，或者你有同学朋友需要，有兴趣就请联系我
你赢我赢，共创双赢
你做代理，可以帮助奥塔哥理工学院同学朋友
你做代理，可以拯救奥塔哥理工学院失足青年
你做代理，可以挽救奥塔哥理工学院一个个人才
你做代理，你将是别人人生奥塔哥理工学院的转折点
你做代理，可以改变自己，改变他人，给他人和自己一个机会顿时留恋起家乡的小河潺潺活水清凉无比日子就这样孤寂而快乐地过着寂寞之余山娃最神往最开心就是晚上无论多晚多累父亲总要携山娃出去兜风逛夜市流光溢彩人潮涌动的都市夜生活总让山娃目不暇接惊叹不已父亲老问山娃想买什么想吃什么山娃知道父亲赚钱很辛苦除了书籍和文具山娃啥也不要能牵着父亲的手满城闲逛他已心满意足了父亲连挑了三套童装叫山娃试穿山娃有点不想父亲说城里不比乡下要穿得漂漂亮亮爸怎么不穿得漂亮望着父亲山娃可
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- 1. STUDENT ID AICTE:-STU63E67B4D60ED21676049229 Full Name:-Besta Abhiram Teja AICTE Email Address:- 228r5a0504@cmrec.ac.in Skills Build Email Address:-bestaabhiramteja@gmail.com Domain:- AI and Machine Learning Organization:- DGT
- 2. AI MENTAL FITNESS TRACKER
- 3. AGENDA TO PREDICT THE MENTAL FITNESS ON THE BASIS OF ‘SCHIZOPHRENIA', ‘BIPOLAR DISORDER', ‘EATING DISORDER',’ANXIETY’,’DRUG USAGE’,’DEPRESSION’,’ALCHOHOL’ USING MACHINE LEARNING REGRESSION MODEL.
- 4. PROJECT OVERVIEW Mental health includes our emotional, psychological, and social well-being. It affects how we think, feel, and act. It also helps determine how we handle stress, relate to others, and make healthy choices. Mental health is important at every stage of life, from childhood and adolescence through adulthood. Here, In this project the Individual's well being Is being predicted by using the past data. By, knowing one’s daily routines and life style and by choosing the right paramenters and comparing It against the past data can help us predict the
- 5. WHO ARE THE END USERS OF THIS PROJECT? The, End users can be Hospitals and other medical centres who wants to predict the mental well being of an Individual. Might be developers who wants to Integrate this Machine Learning model In their project If needed. This ML model might also be used by researchers etc.
- 6. YOUR SOLUTION AND ITS VALUE PROPOSITION As, the output of the dataset Is a numerical value.Regression, models can be used to Implement such tasks. I used, a Random Forest Regressor provided by SK LEARN which fits perfectly with our problem statement. Only, the Input columns which add sense to our data has been chosen to train our model. As, a regression model Is good at dealing with the numerical values. The, regressor predicts the Index of mental fitness of the patient.
- 7. HOW DID YOU CUSTOMIZE THE PROJECT AND MAKE IT YOUR OWN This, entire project has been Implemented from scratch. The datasets were downloaded from the Internet. Pandas was used to read and preprocess the data and the library seaborn was used to find the correlation between the different parameters. The, Values has been scaled using Standard Scaler provided by SK Learn. And Train Test Split was used to obtain Train and Test datasets. The, Random Forest Regressor provided by the SK Learn tool kit was used to Implement the ML Algorithm. And the training has been fit to the ML Model. Finally the test data set were used to make predictions. And the Mean Squared Error was used as the Metrics to evaluate the performance.
- 8. MODELLING Random forest regression is a supervised learning algorithm that uses ensemble learning to create a more accurate and robust regression model than a single decision tree. It does this by training multiple decision trees on different subsets of the data and then averaging the predictions of the trees to get the final prediction. • Bootstrapping: This is the process of randomly sampling the data with replacement. This means that some data points may be sampled multiple times, while others may not be sampled at all. • Random feature selection: This is the process of randomly selecting a subset of features to consider when making a split at each node in the decision tree. Here, In this Project SK Learn’s Random Forest Regressor ML Model Instance was used to solve the problem.
- 9. RESULTS Here, Mean Squared Error was used as a metric to measure the error function of the ML Model and Our Model did pretty well. Here, In the plot shown predicted values were plotted against the real value.
- 10. LINKS Colab Notebook : https://colab.research.google.com/drive/1MUVun7H_72jmmIYMB1a7cY3Wp1GUtLVS?usp=sharing Linkedin:https://www.linkedin.com/in/besta-abhiram-teja- 8424b7234?lipi=urn%3Ali%3Apage%3Ad_flagship3_profile_view_base_contact_details%3BY08VxfgQRBKBS7bm qSFoOg%3D%3D