Author: Admin

Track2Training for students. Learn more on https://track2training.com

VOLUNTEER

Do you have the passion to contribute towards the country’s progress? Join us! You could volunteer with us for a minimum of two hours every week or on and off for events and one-off volunteering opportunities.
Register with us and we will get in touch with you soon (please allow us two weeks) through Email and SMS regarding the next orientation programme. At the orientation you will get more information about all of Bhumi’s projects, the causes you can choose and the locations where you can volunteer.
contact us 
contact@track2training.com

Career

Careers at Track2Training are suitable for dynamic people looking to grow as leaders, capable of functioning as one among our volunteers, enabling and complementing their work. Candidates should be willing to work flexible hours and on weekends. Remuneration is on par with the best in the sector.
Prior experience with volunteer, non-profit, education and /or youth organizations desirable. Prior volunteering experience
Drop a mail to 
contact@track2training.com

INTERNSHIP

We offer internships at Hajipur throughout the year and at other chapters during specific periods. Interns are not provided any remuneration, food or accommodation, but will be equipped with professional skills and provided with a certificate at the end of the engagement.
Interns should be willing to work full time or part time.
Send a mail to contact@track2training.com

About Us

Track2Training (AN INITIATIVE FOR DEVELOPMENT) IS WORKING ON THE DEVELOPMENT OF THE RURAL ECONOMY THROUGH REVIVAL OF THE AGRICULTURE AND COTTAGE INDUSTRY. Creating content for social benefits and sharing knowledge about government schemes and programs for development.


Track2Training (An Initiative for Development) is an active NGO in the city. Hariyali has been carrying out need based welfare and integrated programs of development for rural poor and needy especially belonging to marginalized and under privileged sections. The NGO primarily focus on the development of the rural economy through revival of the agriculture and cottage industry.

Track2Traing  is one of India’s largest independent and youth volunteer non-profit organisations.
Bhumi was founded on 2013 by a small group of professionals with a strong passion to change society today and build a better India for tomorrow. The organisation provides youngsters a platform to serve the society and bridges the gap between the educated and the uneducated.
Our volunteers educate and mentor children from orphanages, slum and village community centres across the country to give them a better future, which will benefit them as well as our country. The learning experience is mutual – our volunteers gain perspective and the experience to mould themselves into tomorrow’s leaders.

ORGANISATION

The organization Hariyali operates through committed and dedicated local women and men workers who have developed support and trust with the communities. The operational strategy includes empowering the poor to become self reliant through continuous experience sharing workshops, exposure visits, skill building and training. Orientation will also be given on livelihood support health, education, biotechnology, animal husbandry and sanitation. The effort shall be made to enhance income through the use of farming systems technology. The organization strongly believes in working with others and learning from others experience and networking with government and local groups. 


Sustainable development in the project shall be emphasized by :

  • Empowering communities through community mobilization.
  • Better opportunities for livelihood improvement.
  • Developing village based institutions.
  • Wider dissemination of lessons learnt and traditional technologies.
  • Experiences sharing workshops with different stakeholders.
  • To generate income of poor rural people by their traditional works like the field of Agriculture / Animal / husbandry / Forest produce value addition etc.
Our philosophy states that India lives in her villages and we cannot rise to our true potential as a country without a fundamental transformation in the lives of people in rural India. At the Swades Foundation we believe that the partnership of rural India with corporates, young urban India, the Government and other foundations is the key to create a permanent and irreversible change for good. 
We aim at bringing together the best global practices, corporate thinking and accountability, the highest standards of corporate governance to create a model of sustainable development, which is a benchmark in the industry and can be replicated at scale. We strongly believe in collaboration and working with multiple partners including other foundations, NGOs, corporates and the government. 
Our Mission is to empower 1 million rural Indians every 5 years, creating a permanent, irreversible change for good. We believe in a holistic 360-degree development with a focus on six verticals – Community Mobilisation, Water & Sanitation, Agriculture & Dairy, Livelihood, Education and Health & Nutrition. This model empowers our communities with the capability of creating choices for themselves and their families, allowing them to transform their own lives and ensuring a permanent and irreversible change for good 
Our strategy is to Engage, Empower, Execute and Exit: To engage rural communities with corporates, young urban India, not-for-profit organizations and governments and empower our communities to execute programs that transform their own lives, enabling us to exit and allowing them to serve as role models and change agents for the rest of the country. 

Areas of Interest

  1. Capacity building                 
  2. Monitoring & evaluation      
  3. Micro – enterprises establishment
  4. Watershed works.
  5. Sanitation works.
  6. Sericulture activities.
  7. Lac cultivation, processing & marketing.
  8. Animal husbandry
  9. Micro planning. 
  10. Child Development MDM ,Diet Plan

INFRASTRUCTURE AND FACILITIES

OFFICE : Our organization has well established Office, Training centre & Vehicles.
EQUIPMENT : 1. Telephone, Fax Machine ,Computers and  Printers available.
2. LCD Projector time for video visuals trainings  to peoples.
3. Having documentary films on watershed, sanitation, education, health,  veterinary, agricultural fields.

Contact

Send us a mail to editor@edupu.org

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What is Factor Analysis Method

 Factor analysis is a statistical technique used to identify underlying factors or latent variables that explain the patterns of correlations among a set of observed variables. It’s widely employed in psychology, sociology, economics, and other fields where researchers seek to understand complex relationships between variables.

Here’s an overview of the process involved in factor analysis:

  1. Define the Research Question: Before conducting factor analysis, researchers need to have a clear understanding of the research question they want to address. They should identify the variables of interest and hypothesize about the underlying factors that may be influencing those variables.

  2. Data Collection: Researchers collect data on the variables of interest from a sample population. These variables could be anything from survey responses to physical measurements.

  3. Data Preparation: The collected data are then prepared for factor analysis. This may involve checking for missing values, assessing data quality, and ensuring that the variables are suitable for analysis (e.g., continuous variables, normally distributed).

  4. Choose the Factor Analysis Method: There are different types of factor analysis methods, including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA is used when researchers don’t have preconceived ideas about the underlying factors, while CFA is used to test a specific hypothesis about the structure of the factors. Researchers select the appropriate method based on their research goals and the nature of the data.

  5. Factor Extraction: In EFA, this step involves extracting the initial set of factors from the data. Common techniques for factor extraction include principal component analysis (PCA) and principal axis factoring (PAF). These techniques identify linear combinations of variables that account for the maximum amount of variance in the data. The number of factors to extract can be determined based on statistical criteria (e.g., eigenvalues, scree plot) or theoretical considerations.

  6. Factor Rotation: Once the initial factors are extracted, researchers often apply factor rotation to simplify the interpretation of the factors. Rotation methods, such as varimax and oblimin, reorient the factors in a way that maximizes the variance of loadings (the correlations between variables and factors) and makes the factors easier to interpret.

  7. Interpretation: After rotation, researchers interpret the meaning of each factor based on the pattern of loadings. High loadings (positive or negative) indicate strong relationships between variables and factors, suggesting that the variables are influenced by the underlying factor. Researchers may label each factor based on the variables with high loadings and develop theories to explain the relationships between factors and variables.

  8. Assessment of Model Fit (CFA): In confirmatory factor analysis, researchers assess the fit of the hypothesized factor structure to the data using various fit indices (e.g., chi-square, comparative fit index, Tucker-Lewis index). This step involves comparing the observed data with the model-implied covariance matrix to determine how well the model fits the data.

  9. Reporting Results: Finally, researchers report the results of the factor analysis, including the number of factors extracted, the pattern of factor loadings, and any additional analyses conducted to validate the findings. They may also discuss the implications of the results for theory and practice in their respective fields.

Factor analysis is a powerful tool for uncovering the underlying structure of complex datasets, providing researchers with valuable insights into the relationships between variables and helping to advance knowledge in various disciplines.

Top Educational Management tools for Teachers

 Several educational management tools are invaluable for teachers, enhancing efficiency, organization, and communication within classrooms. Here are some top picks:

  1. Google Classroom: This platform integrates seamlessly with Google Workspace (formerly G Suite) and allows teachers to create, distribute, and grade assignments digitally. It facilitates communication with students, provides a centralized location for resources, and offers collaboration features.

  2. Canvas: Canvas is a learning management system (LMS) that offers a wide range of tools for course management, including assignment creation, grading, discussions, and multimedia content integration. It provides a customizable interface and supports mobile access for both teachers and students.

  3. Schoology: Schoology is another popular LMS that streamlines classroom management tasks such as lesson planning, grading, and communication. It offers features for creating interactive assignments, quizzes, and discussions, as well as tools for tracking student progress and performance.

  4. Edmodo: Edmodo is a user-friendly platform that enables teachers to create a virtual classroom environment for engaging students in discussions, assignments, and collaborative projects. It also offers features for parent communication and professional development.

  5. Microsoft Teams: Teams is a collaboration platform that integrates with Microsoft Office 365, providing tools for communication, file sharing, and project management. It allows teachers to host virtual meetings, share resources, and collaborate with students in real time.

  6. ClassDojo: ClassDojo is a communication platform that strengthens the connection between teachers, students, and parents. It offers features for behavior tracking, messaging, and sharing updates and announcements, fostering a positive classroom culture.

  7. Remind: Remind is a messaging app designed specifically for communication between teachers, students, and parents. It allows teachers to send announcements, reminders, and assignments via text message or email, ensuring that important information reaches everyone efficiently.

  8. Nearpod: Nearpod is an interactive presentation platform that engages students with multimedia content, polls, quizzes, and collaborative activities. It allows teachers to create dynamic lessons and assess student understanding in real time.

  9. Kahoot!: Kahoot! is a game-based learning platform that makes learning fun and interactive. Teachers can create quizzes, surveys, and discussions to assess student knowledge and engagement, fostering a competitive yet supportive learning environment.

  10. Flipgrid: Flipgrid is a video discussion platform that encourages student voice and participation. Teachers can create discussion prompts, and students respond with short video clips, promoting communication and collaboration among classmates.

These educational management tools empower teachers to streamline administrative tasks, enhance communication and collaboration, and create engaging learning experiences for their students. By leveraging these tools effectively, teachers can maximize their impact in the classroom and support student success.

18 Free Exploratory Data Analysis Tools

Some of these tools are even better than programming (R, Python, SAS) tools.

All of us are born with special talents. It’s just a matter of time until we discover it and start believing in ourselves. We all have limitations, but should we stop there? No.

When I started coding in R, I struggled. Sometimes a lot more than one can ever think! Because I had never ever coded even  in my entire life.  My situation was similar to a guy who didn’t know swimming but was manhandled into deep ocean, who somehow saved himself from drowning but ended up gulping lot of salty water.

Now when I look back, I laugh at myself. Do you know why? Because, I could have chosen one of several non-coding tools available for data analysis, and could’ve avoided the suffering.

Data exploration is an inevitable part of predictive modeling. You can’t make predictions unless you know what happened in the past. The most important skill to master data exploration is ‘curiosity’, which is free of cost yet isn’t owned by everyone.

I have written this article to help you acknowledge various free tools available for exploratory data analysis. Now a days, ample of tools are available in the market which are free & quite interesting to work with. These tools doesn’t require you to code explicitly but simple drag – drop clicks do the job.

List of  Non Programming Tools

1. Excel / SpreadsheetExcel, data analytics

If you are transitioning into data science or have already survived for years, you would know, even after countless years, excel remains an indispensable part of analytics industry. Even today, most of the problems faced in analytics projects are solved using this software. With larger than ever community support, tutorials, free resources, learning this tool has become quite easier.

It supports all the important features like summarizing data, visualizing data, data wrangling etc. which are powerful enough to inspect data from all possible angles. No matter how many tools you know, excel must feature in your armory. Though, Microsoft excel is paid but you can still try various other spreadsheet tools like open office, google docs, which are certainly worth a try!

Free Download: Click Here

 

2. Trifactatrifacta, data cleaning

Trifacta’s Wrangler tool is challenging the traditional methods of data cleaning and manipulation. Since Excel possess limitations on data size, this tool has no such boundaries and you can securely work on big data sets. This tool has incredible features such as chart recommendations, inbuilt algorithms, analysis insights using which you can generate reports in no time. It’s an intelligent tool focused on solving business problems faster, thereby allowing us to be more productive at data related exercises.

Availability of such open source tools make us feel more confident and supportive, also that there are good people around the world who are working extremely hard to make our lives better.

Free Download: Click Here

 

3. Rapid Minerrapid miner, machine learning

This tool emerged as a leader in 2016 Gartner Magic Quadrant for Advanced Analytics. Yes, it’s more than a data cleaning tool. It extends its expertise in building machine learning models. Yes, it comprises all the ML algorithms which we use frequently. Not just a GUI, it also extends support to people using Python & R for model building.

It continues to fascinate people around the world with its remarkable capabilities. Above all, it claims to provide analytics experience at lightning fast level. Their product line has several products built for big data, visualizations, model deployment, some of which (enterprise) include a subscription fee. In short, we can say it’s a complete tool for any business which requires performing all tasks from data loading to model deployment.

Free Download: Click Here

 

4. Rattle GUI rattle, R

If you tried using R, but couldn’t get a knack of what’s going in, Rattle should be your first choice. This GUI is built on R and gets launched by typing install.packages("rattle") followed by library(rattle) then rattle() in R. Therefore, to use Rattle you must install R. It’s also more than just data mining tool. Rattle supports various ML algorithms such as Tree, SVM, Boosting, Neural Net, Survival, Linear models etc.

It’s being widely used these days. According to CRAN, Rattle is being installed 10000 times every month. It provides enough options to explore, transform and model data in just a few clicks. However, it has fewer options than SPSS for statistical analysis. Although, SPSS is a paid tool while Rattle is free of cost.

Free Download: Click Here

 

5. Qlikviewqlikview, business intelligence

Qlikview is one of the most popular tools in the business intelligence industry around the world. Deriving business insights and presenting it in an awesome manner, is what this tool does. With it’s state of the art visualization capabilities, you’d be amazed by the amount of control you get while working on data. It has an inbuilt recommendation engine to update you from time to time about the best visualization methods while working on data sets.

However, it is not a statistical software. Qlikview is incredible at exploring data, trends, insights but it can’t prove anything statistically. In that case, you might want to look at other softwares.

Free Download: Click Here

 

6. Weka weka, machine learning

An advantage of using Weka is that it is easy to learn. Being a machine learning tool, its interface is intuitive enough for you to get the job done quickly. It provides options for data preprocessing, classification, regression, clustering, association rules and visualization. Most of the steps you think of while model building can be achieved using Weka. It is built on Java.

Initially, it was designed for research purposes at University of Wakaito, but later it got accepted by more and more people around the world. However, over time I haven’t seen an enthusiastic Weka community like that of R and Python. The tutorial listed below should help you more.

Free Tutorial: Click Here

 

7. KNIME knime, machine learning, data visualization

Similar to RapidMiner, KNIME offers an open source analytics platform for analyzing data, which can later be deployed, scaled using other supportive KNIME products. This tool has an abundance of features on data blending and visualization, and advanced machine learning algorithms. Yes, using this tool you can build models as well. Although, there hasn’t been enough talk about this tool, but considering its state of the art design, I think it will soon come under much needed limelight.

Moreover, quick training lessons are available on their website to get you started with this tool right now.

Free Download: Click Here

 

8. Orange orange, machine learning, data cleaning

As cool as its sounds, this tool is designed to produce interactive data visualizations and data mining tasks. There are enough youtube tutorials to learn this tool. It has an extensive library of data mining tasks which includes all classification, regression, clustering methods. Along with this, the versatile visualizations which get formed during data analysis allow us to understand the data more closely.

To build any model, you’ll be required  to create a flowchart. This is interesting as it would help us further understand the exact procedure of data mining tasks.

Free Download: Click Here

 

9. Tableau Publictableau, data visualization

Tableau is a data visualization software. We can say, tableau and qlikview are the most powerful sharks in the business intelligence ocean. The comparison of superiority is never ending. It’s a fast visualization software which let’s you explore data, every observation using various possible charts. It’s intelligent algorithms figure out by self about the type of data, best method available etc.

If you want to understand data in real time, tableau can get the job done. In a way, tableau imparts a colorful life to data and let’s us share our work with others.

Free Download: Click Here

 

10. Data Wrapper datawrapper, business intelligence, data visualization

It’s a lightning fast visualization software. Next time, when someone in your team gets assigned BI work, and he/she has no clue what to do, this software is a considerable option. It’s visualization bucket comprises of line chart, bar chart, column chart, pie chart, stacked bar chart and maps. So, it’s a basic software and can’t be compared with giants like tableau and qlikview. This tool is browser enabled and doesn’t require any software installation.

 

11. Data Science Studio (DSS)

ikuIt is a powerful tool designed to connect technology, business and data. It is available in two segments: Coding & Non-Coding. It’s a complete package for any organization which aims to develop, build, deploy and scale models on network. DSS is also powerful enough to create smart data applications to solve real world problems. It comprises of features which facilitates team integration on projects. Among all features, the most interesting part is, you can reproduce your work in DSS as every action in the system is versioned through an integrated GIT repository.

Free Download: Click Here

 

12. OpenRefinerefine

It started as Google Refine but looks like google plummeted this project due to reasons unclear. However, this tool is still available renamed as Open Refine. Among the generous list of open source tools, openrefine specializes in messy data; cleaning, transforming and shaping it for predictive modeling purposes. As an interesting fact, during model building, 80% time of an analyst is spent in data cleaning. Sounds unpleasant, but it’s a fact. Using openrefine, analysts can not only save their time, but put it to use for productive work.

Free Download: Click Here

 

13. Talendtalend

Decision making these days is largely driven by data. Managers & professionals no longer take gut-based decisions. They require a tool which can help them quickly. Talend can help them to explore data and support their decision making. Precisely, it’s a data collaboration tool capable of clean, transform and visualize data.

Moreover, it also offers an interesting automation feature where you can save and redo your previous task on a new data set. This feature is unique and haven’t been found in many tools. Also, it makes auto discovery, provides smart suggestion to the user for enhanced data analysis.

Free Download: Click Here

 

14. Data Preparator data preparator, data cleaning

This tool is built on Java to assist us in data exploration, cleaning and analysis. It includes various inbuilt packages for discretization, numeration, scaling, attribute selection, missing values, outliers, statistics, visualization, balancing, sampling, row selection, and several other tasks. It’s GUI is intuitive and simple to understand. Once you start working on it, I’m sure you wouldn’t take lot of time to figure out how to work.

A unique advantage of this tool is, the data set used for analysis doesn’t get stored in computer memory. This means you can work on large data sets without having any speed or memory troubles.

Free Download: Click Here

 

15. DataCracker  datacracker, messy data, survey data

It’s a data analysis software which specializes on survey data. Many companies do survey but they struggle to analyze it statistically. Survey data are never clean. It comprises of multiple missing & inappropriate values. This tool reduces our agony and enhances our experience of working on messy data. This tool is designed such that it can load data from all major internet survey programs like surveymonkey, survey gizmo etc. There are several interactive features which helps to understand data better.

Free Download: Click Here

 

16. Data Applied data_applied, data visualization, data mining

This powerful interactive tool is designed to build, share, design data analysis reports. Creating visualization on large data sets can sometimes be troublesome. But this tool is robust in visualizing large amounts of data using tree maps. Like all other tools above, it has feature for data transformation, statistical analysis, detecting anomalies etc. All in all, it’s a multi usage data mining tool capable of of automatically extracting valuable knowledge (signal) from the raw data. You’d be amazed to see that such non-programming tools are no less than R or Python for data analysis.

Free Download: Click Here

 

17.  Tanagra Project tanagra

You might not like it because of its old fashioned UI, but this free data mining software is designed to build machine learning models. Tanagra project started as a free software for academic and research purposes. Being an open source project, it provides you enough space to devise your own algorithm and contribute.

Along with supervised learning algorithms, it is enabled with paradigms such as clustering, factorial analysis, parametric and nonparametric statistics, association rule, feature selection and construction algorithms etc. Some of its limitations include  unavailability of wide set of data sources, direct access to datawarehouses and databases, data cleansing, interactive utilization etc.

Free Download: Click Here

 

18. H2oh2o, machine learning

H2o is one of the most popular software in analytics industry today. In few years, this organization has succeeded in evangelizing the analytics community around the world. With this open source software, they bring lighting fast analytics experience, which is further extended using API for programming languages. Not just data analysis, but you can build advanced machine learning models in no time. The community support is great, hence learning this tool isn’t a worry. If you live in US, chances are they would be organizing a meetup nearby you. Do drop by!

Free Download: Click Here

 

Bonus Additions:

In addition to the awesome tools above, I also found some more tools which I thought you might be interested to look at. However, these tools aren’t free but you can still avail them for trial:

  1. Data Kleenr
  2. Data Ladder
  3. Data Cleaner
  4. WinPure