AnalyticBridge2014-08-21T21:58:31ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebelhttp://api.ning.com/files/sjiEmaLbXGhN1WRavJqWDhDVVRgy98r*r9QjzvuoTYRjxre6-ZcjLQ1TRSiubt*zolu3-UJFBpr3FQYTbYas*9Xfbs8SCfiF/smaller.jpg?width=48&height=48&crop=1%3A1http://www.analyticbridge.com/forum/topic/listForContributor?user=mryrtp6jl4nl&feed=yes&xn_auth=noEasiest way to learn machine learning.tag:www.analyticbridge.com,2014-08-18:2004291:Topic:3054682014-08-18T07:00:25.482ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>There are some excellent resources here. But, I thought, the more helpful approach might be a plan and hence am adding one more answer to this list.</p>
<p>My goal is to create a plan where you get to the level of average industry practitioner</p>
<p>Skills you need: Ability to take Excel/CSV data sets, pre-process and visualize; Build a model and Visualize the results</p>
<p>Recommended steps:</p>
<p>1. Download one data set from Kaggle/UCI or anywhere from the Internet. I am deliberately…</p>
<p>There are some excellent resources here. But, I thought, the more helpful approach might be a plan and hence am adding one more answer to this list.</p>
<p>My goal is to create a plan where you get to the level of average industry practitioner</p>
<p>Skills you need: Ability to take Excel/CSV data sets, pre-process and visualize; Build a model and Visualize the results</p>
<p>Recommended steps:</p>
<p>1. Download one data set from Kaggle/UCI or anywhere from the Internet. I am deliberately not giving a link as I want you to search through multiple sets. Create a deck of slides describing the business problem, ROI, current practices, their weakness etc.</p>
<p>Mile stone 1: Creating a business context for a problem is a crucial step in becoming a practitioner. Congrats, you have done that! You should spend a week for this provided you put in 20 hours a week.</p>
<p>2. Look at the attributes given. Brain storm whether you can create more attributes from them. If transactions are given, you can create average number of transaction per day, average value of transactions etc. Think and create as many new attributes as you can.<br/> 2. Download R, Deducer (my preference). They both are open source.<br/> 3. From the resources provided by others, learn the techniques and intuition behind standard data pre-processing (I mean ways in which you fill missing values, bin neumeric variables and merge categorical variables, scale data, dimensionality reduction etc.).<br/> 4. Use Excel/Deducer and create new data and pre-process the data.</p>
<p>Mile stone 2: Creating one big structured table where independent attributes are columns and records are rows is a huge step in solving. You should be able to do this with 4 weeks of work. Don’t forget to add a few slides in your ppt on data pre-processing</p>
<p>5. Learn descriptive statistics, histogram, box plot, scatter plot and bar chart. Learn to plot these in deducer/ggplot.<br/> 6. Do detailed descriptive statistics and visualizations on the data. There are excellent resources on this all over the net. I created a few videos myselg (<a href="http://beyond.insofe.edu.in/cate">http://beyond.insofe.edu.in/cate</a>…)</p>
<p>Mile stone 3: Visualizing is considered most important interfacing step. and you are done with it. Add these to your slide deck. Allocate two weeks for this.</p>
<p>6. Learn linear, logistic regression and clustering from any of the resources given in these threads.<br/> 7. Apply then on your data sets and do all diagnostics. Deducer makes it easy to do this.</p>
<p>Mile stone 4: Congrats! You built your predictive models. I think, you need 3 weeks for this step.</p>
<p>8. Brain storm and think about how you can simplify and present these results. Goal is to present to a non-data scientist. Use your visualization skills again. Add these slides to your deck.</p>
<p>Milestone 5: Take a week or two for this.</p>
<p>You have created a slide deck, some code and knowledge base. Nore importantly, you solved a problem end-to-end. Viola, in approximately 12 weeks you are where 90% of data scientists are <img src="http://beyond.insofe.edu.in/wp-includes/images/smilies/icon_smile.gif" alt=":-)" class="wp-smiley"/></p>
<p>Now, to get to a higher level</p>
<p>Add more algorithms (decision trees, neural nets etc.). Learn more domains and problems. Study techniques to solve unstructured data. There are wonderful courses in the thread. Take them slowly.</p>
<p>Hope this helps.</p> Challenge of the week - Modeling and explaining the law of seriestag:www.analyticbridge.com,2014-08-09:2004291:Topic:3042292014-08-09T01:18:01.534ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>We posted an article last week, proving with Monte-Carlo simulations the fact that events (accidents, casino winnings) tend to appear in clusters, with long accident-free time periods between clusters. A cluster is defined as a short time period with many accidents.</p>
<p><a href="http://www.datasciencecentral.com/profiles/blogs/the-law-of-series-why-4-plane-crashing-in-6-months-is-a-coinciden" target="_blank">Here's the article</a>, and below is its first sentence:</p>
<p><em>Very short…</em></p>
<p>We posted an article last week, proving with Monte-Carlo simulations the fact that events (accidents, casino winnings) tend to appear in clusters, with long accident-free time periods between clusters. A cluster is defined as a short time period with many accidents.</p>
<p><a href="http://www.datasciencecentral.com/profiles/blogs/the-law-of-series-why-4-plane-crashing-in-6-months-is-a-coinciden" target="_blank">Here's the article</a>, and below is its first sentence:</p>
<p><em>Very short time periods (6 months) with several [plane]crashes, as well as long time periods (3 years) with no crashes are expected. An even distribution of plane crashes is indeed NOT expected - it would look very suspicious, and definitely not random.</em></p>
<p><span><img src="http://api.ning.com/files/zR-FkEEcSb9RmXL6zOgPXVw9XUDCnWT-qVr0qke7nJkI5oebMrXH7qVLCAzGI5BCgH0H87qcEwOFD9ElIz6XkBa3GoirQ*Dc/bor55.PNG" class="align-center"/></span></p>
<p>In this challenge, we ask you to read our proposed explanation and <a href="http://api.ning.com/files/zR-FkEEcSb8r7*vfdW0Bq7ekwDJ7s-fk64ct-YsmGFhtZZFB1PkEwBHeUehxXx7ZQVcUO2*7YrR2fAZUdlv1ODwmRgAZVTjb/PlaneCrashes.xlsx" target="_self">spreadsheet</a> (the spreadsheet password is 5150), and then come up with a real mathematical / statistical explanation, not just Monte-Carlo simulations like we did. Our article provide hints about <a href="http://www.datasciencecentral.com/profiles/blogs/the-law-of-series-why-4-plane-crashing-in-6-months-is-a-coinciden" target="_blank">developing a theoretical solution</a>. This is an exciting data science topic.</p>
<p>Anyone who posts a sound statistical explanation is entitled to a free, signed copy of my <a href="http://www.datasciencecentral.com/profiles/blogs/my-data-science-book" target="_blank">data science book</a>: Email me at vincentg@datasciencecentral.com with the subject line "Law of Series Challenge" to receive your copy.</p>
<p><a href="http://www.analyticbridge.com/forum/topics/challenge-of-the-week-time-series" target="_blank">Click here</a> to check out our previous challenge of the week.</p> Currently the hot topics in Machine Learning research and in real applications.tag:www.analyticbridge.com,2014-08-07:2004291:Topic:3039212014-08-07T10:26:51.213ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>In general the following are fairly hot in machine learning and data science communities that are interested in modeling:</p>
<p>Deep learning: This seems to be breaking all benchmarks in accuracies in a variety of complex problems.<br></br> NLP: Understanding sentiment, sarcasm, urgency and summarizing free flowing text are being studied extensively.<br></br> Spectral methods and Kernel methods driven modeling methods are always hot problems.</p>
<p>From an engineering perspective, there is a lot…</p>
<p>In general the following are fairly hot in machine learning and data science communities that are interested in modeling:</p>
<p>Deep learning: This seems to be breaking all benchmarks in accuracies in a variety of complex problems.<br/> NLP: Understanding sentiment, sarcasm, urgency and summarizing free flowing text are being studied extensively.<br/> Spectral methods and Kernel methods driven modeling methods are always hot problems.</p>
<p>From an engineering perspective, there is a lot of emphasis in building newer visualization tools and techniques. Of course, I see a new engineering model of big data every week.</p>
<p></p> Solution for pharmaceutical industrytag:www.analyticbridge.com,2014-08-06:2004291:Topic:3040672014-08-06T05:21:13.170ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p><a href="http://api.ning.com:80/files/cwh76f0JjbljoLbge8WTRl3ius7FEX1B5XUYIByhVVqzFTSIMJbWTKLv45SkFa595IASVBKUP7RiithqWl8R7QEUAKKCl7ss/CT.png" target="_self"><img class="align-full" src="http://api.ning.com:80/files/cwh76f0JjbljoLbge8WTRl3ius7FEX1B5XUYIByhVVqzFTSIMJbWTKLv45SkFa595IASVBKUP7RiithqWl8R7QEUAKKCl7ss/CT.png" width="149"></img></a> <span style="font-size: 8px; color: #666666;">Image taken from <a href="http://ehealth.eletsonline.com/wp-content/uploads/2013/03/CT.jpg" style="color: #666666;" target="_blank">eletsonline.com</a></span></p>
<p>INSOFE scientists developed novel algorithms that could be used by pharmaceutical industry to check fraud in…</p>
<p><a target="_self" href="http://api.ning.com:80/files/cwh76f0JjbljoLbge8WTRl3ius7FEX1B5XUYIByhVVqzFTSIMJbWTKLv45SkFa595IASVBKUP7RiithqWl8R7QEUAKKCl7ss/CT.png"><img class="align-full" src="http://api.ning.com:80/files/cwh76f0JjbljoLbge8WTRl3ius7FEX1B5XUYIByhVVqzFTSIMJbWTKLv45SkFa595IASVBKUP7RiithqWl8R7QEUAKKCl7ss/CT.png" width="149"/></a><span style="font-size: 8px; color: #666666;">Image taken from <a href="http://ehealth.eletsonline.com/wp-content/uploads/2013/03/CT.jpg" target="_blank" style="color: #666666;">eletsonline.com</a></span></p>
<p>INSOFE scientists developed novel algorithms that could be used by pharmaceutical industry to check fraud in clinical trials. Typically, Pharma companies follow a tedious, semi-manual approach to solve this all important (billion dollar) problem. What makes it difficult is the low occurrence (1 in 100,000 records). But, we developed algorithms that can plough through millions of records, identify every possible instance of fraud and present them in a easy to use manner for the operational person (typically a non-mathematician). The algorithms are being tested on real data and results are very encouraging.</p> Two perfectly round circlestag:www.analyticbridge.com,2014-08-01:2004291:Topic:3027112014-08-01T18:18:13.137ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>How do you explain this illusion?</p>
<p><a href="http://api.ning.com:80/files/Tkccsb*3vm7CZsxLTR9TDj*C6h65HAa4qG*jFsVwvtPaj0wY31JVcQK6PI0uWpzvUu22ZfWup1MNQ4NGy*dIsSJJ40uaU0kN/bor55.PNG" target="_self"><img width="339" class="align-full" src="http://api.ning.com:80/files/Tkccsb*3vm7CZsxLTR9TDj*C6h65HAa4qG*jFsVwvtPaj0wY31JVcQK6PI0uWpzvUu22ZfWup1MNQ4NGy*dIsSJJ40uaU0kN/bor55.PNG"/></a></p>
<p></p>
<p>How do you explain this illusion?</p>
<p><a href="http://api.ning.com:80/files/Tkccsb*3vm7CZsxLTR9TDj*C6h65HAa4qG*jFsVwvtPaj0wY31JVcQK6PI0uWpzvUu22ZfWup1MNQ4NGy*dIsSJJ40uaU0kN/bor55.PNG" target="_self"><img width="339" class="align-full" src="http://api.ning.com:80/files/Tkccsb*3vm7CZsxLTR9TDj*C6h65HAa4qG*jFsVwvtPaj0wY31JVcQK6PI0uWpzvUu22ZfWup1MNQ4NGy*dIsSJJ40uaU0kN/bor55.PNG"/></a></p>
<p></p> Best way to leverage a sports prediction model?tag:www.analyticbridge.com,2014-07-31:2004291:Topic:3027952014-07-31T19:05:35.764ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>I've been working on a model to predict the outcome of certain sporting events. It started as a for-fun side project which I didn't really expect to succeed - but over the last 6 months the model has performed surprisingly well. Now I'm wondering what to do with it. So far all I've come up with is:</p>
<ul>
<li>Start making bets (I have a bit of an ethical qualm with this one)</li>
<li>Start making bets and donate profits to charity (maybe <em>Gamblers Anonymous</em> for an ironic…</li>
</ul>
<p>I've been working on a model to predict the outcome of certain sporting events. It started as a for-fun side project which I didn't really expect to succeed - but over the last 6 months the model has performed surprisingly well. Now I'm wondering what to do with it. So far all I've come up with is:</p>
<ul>
<li>Start making bets (I have a bit of an ethical qualm with this one)</li>
<li>Start making bets and donate profits to charity (maybe <em>Gamblers Anonymous</em> for an ironic flair)</li>
<li>Publish it in an academic journal as evidence of betting market inefficiencies, etc.</li>
<li>Publicize the predictions and watch the effect on gamblers' decisions, as a sort of social experiment</li>
</ul>
<p>Do you have any more creative (or more profitable) ideas?</p>
<p>Thanks!</p> Challenge of the Week - Time Series and Spatial Processestag:www.analyticbridge.com,2014-07-24:2004291:Topic:3024582014-07-24T05:13:06.061ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>This is a mathematical challenge, thought it is related to statistical parameter estimation in the context of time series / auto-regressive processes, such as ARMA. No prior advanced calculus knowledge necessary - smart high school kids can find the solution, thought it's not trivial!…</p>
<p><a href="http://api.ning.com:80/files/Q9JKAyO9-k7UaOU960qro*DwAKMnh6h4Aham9H-eJZC2RXLfU3sTwXEopBV*0X4CfClRgFwb0t0xcWIj-Kx9AH6-e9JLl7yA/bor55.PNG" target="_self"><img class="align-center" src="http://api.ning.com:80/files/Q9JKAyO9-k7UaOU960qro*DwAKMnh6h4Aham9H-eJZC2RXLfU3sTwXEopBV*0X4CfClRgFwb0t0xcWIj-Kx9AH6-e9JLl7yA/bor55.PNG" width="557"></img></a></p>
<p>This is a mathematical challenge, thought it is related to statistical parameter estimation in the context of time series / auto-regressive processes, such as ARMA. No prior advanced calculus knowledge necessary - smart high school kids can find the solution, thought it's not trivial!</p>
<p><a href="http://api.ning.com:80/files/Q9JKAyO9-k7UaOU960qro*DwAKMnh6h4Aham9H-eJZC2RXLfU3sTwXEopBV*0X4CfClRgFwb0t0xcWIj-Kx9AH6-e9JLl7yA/bor55.PNG" target="_self"><img width="557" class="align-center" src="http://api.ning.com:80/files/Q9JKAyO9-k7UaOU960qro*DwAKMnh6h4Aham9H-eJZC2RXLfU3sTwXEopBV*0X4CfClRgFwb0t0xcWIj-Kx9AH6-e9JLl7yA/bor55.PNG"/></a></p>
<p style="text-align: center;"><em><a href="https://github.com/datawrangling/spatialanalytics" target="_blank">Click here</a> for picture source </em></p>
<p>Let's say that we have the model X(t) = <strong>a</strong> X(t-1) + <strong>b</strong> X(t-2) + e, where e is a white, independent noise (random variable) with zero mean, and t is the time. In short, a basic auto-regressive process or time series. More complex models are considered below.</p>
<p>The questions are as follows:</p>
<ol>
<li>What constrainsts should we put on <strong>a</strong> and <strong>b</strong> to guarantee that the model is sound?</li>
<li>What statistical inference techniques offer solutions satisfying the above conditions? </li>
</ol>
<p>Example: Let's assume that X(0) = 1, X(1) = 1, and for the sake of simplicity, let's assume that e = 0. Clearly if <strong>a</strong>=0.5 and <strong>b</strong>=0.5, then X(t) is constant, always equal to 1 no matter the value of t. If <strong>a</strong>=1 and <strong>b</strong>=1, then X(t) quickly becomes infinite as t grows.</p>
<p>We have the following potential cases for X(t), depending on <strong>a</strong> and <strong>b</strong>:</p>
<ul>
<li>Polynomial growth (including linear or constant)</li>
<li>Exponential growth (with or without wild oscillations)</li>
<li>Converging to 0</li>
<li>Stable and non-periodic</li>
<li>Stable and periodic</li>
</ul>
<p>Question: what are the parameter sets driving stability?</p>
<p>The model X(t) = <strong>a</strong> X(t-1) + <strong>b</strong> X(t-2) + e has the following characteristic equation:</p>
<p style="text-align: center;">x^2 - a*x - b = 0.</p>
<p>The solutions to this equation (as well as initial conditions X(0) and X(1)) entirely determines whether X(t) is stable or not. Let's denote as r and s the two solutions of this characteristic equation:</p>
<ul>
<li>If r=s, we get linear or no growth for X(t).</li>
<li>If |r| and |s| are < 0, then X(t) converges to 0 as t grows.</li>
<li>If |r| or |s| > 0, we might experience exponential growth.</li>
</ul>
<p><strong>Challenge</strong></p>
<ul>
<li>Formalize conditions to be satisfied by <strong>a</strong> and <strong>b</strong>, to guarantee long-term stability</li>
<li>Identify statistical techniques (<a href="http://www.datasciencecentral.com/profiles/blogs/10-types-of-regressions-which-one-to-use" target="_blank">regression</a>, Box-Jenkins) producing estimates that meet the previous conditions. Show that most traditional statistical (econometrics) inference techniques actually fail to meet the condition, and are thus only good for very short-term predictions.</li>
<li>Generalize to X(t) = <strong>a</strong> X(t-1) + <strong>b</strong> X(t-2) + <strong>c</strong> X(t-3) + noise</li>
<li>Generalize to spatial processes, for instance an image with pixel interactions with neighbor pixels: X(t, u) = <strong>a</strong> X(t-1, u) + <strong>b</strong> X(t+1, u) + <strong>c</strong> X(t, u-1) + <strong>d</strong> X(t, u+1) + noise</li>
</ul>
<p>Perform monte carlo simulations with various values of <strong>a</strong>, <strong>b</strong>, X(0) and X(1) to simulate these auto-regressive time series (can be done in Excel, R, Perl, Matlab or Python), to confirm your findings.</p>
<p><strong>Former weekly challenge</strong></p>
<ul>
<li><a href="http://www.analyticbridge.com/forum/topics/challenge-of-the-week-random-numbers" target="_blank">Random numbers generation</a></li>
</ul>
<p></p> Challenge of the week: can monkeys use a currency?tag:www.analyticbridge.com,2014-07-17:2004291:Topic:3014992014-07-17T05:31:34.783ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>How would you go about proving that some mokeys can use a currency (let's say actual one dollar bills) to buy food and privileges? What kind of experimental design would you set up to test this hypothesis? And what about testing if some alpha-monkeys are going to "steal" money from their fellows, and create their own "bank", to control and leverage the money? Will they use the money for prostitution and other bad purposes (hiring a hit man - I mean a hit monkey?)…</p>
<p></p>
<p>How would you go about proving that some mokeys can use a currency (let's say actual one dollar bills) to buy food and privileges? What kind of experimental design would you set up to test this hypothesis? And what about testing if some alpha-monkeys are going to "steal" money from their fellows, and create their own "bank", to control and leverage the money? Will they use the money for prostitution and other bad purposes (hiring a hit man - I mean a hit monkey?)</p>
<p><a href="http://api.ning.com:80/files/3A8rUyA9jKOXkJVm0W*yJvm*5oHAlQZCdWWMZShN8FUw0NJGmC9-inBm*Vo3SyZ3x1iZ6mPVOcTXQV7w5yf6I5w8WVshpiyZ/bor55.PNG" target="_self"><img src="http://api.ning.com:80/files/3A8rUyA9jKOXkJVm0W*yJvm*5oHAlQZCdWWMZShN8FUw0NJGmC9-inBm*Vo3SyZ3x1iZ6mPVOcTXQV7w5yf6I5w8WVshpiyZ/bor55.PNG" width="340" class="align-center"/></a></p>
<p style="text-align: center;"><em>Do you think this guy is some sort of Madoff or <a href="http://en.wikipedia.org/wiki/Dominique_Strauss-Kahn" target="_blank">DSK</a>?</em></p>
<p><a href="http://www.analyticbridge.com/forum/topics/challenge-of-the-week-random-numbers" target="_blank">Read our previous challenge of the week</a></p>
<p></p> How best to leverage a database of the 40,000 richest people in the country?tag:www.analyticbridge.com,2014-07-06:2004291:Topic:3006992014-07-06T05:41:46.266ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>Hello,</p>
<p>I need your advice on a question related to data.</p>
<p></p>
<p><strong>Background:</strong> I work with a luxury magazine which covers three areas namely fashion, interior design/architecture and lifestyle. In order to maintain exclusivity the magazine cannot be purchased in a book store. It is circulated to a subscriber base of 40,000 readers, who are carefully selected depending on their income and social status to see if they fit the target audience of the magazine. As a…</p>
<p>Hello,</p>
<p>I need your advice on a question related to data.</p>
<p></p>
<p><strong>Background:</strong> I work with a luxury magazine which covers three areas namely fashion, interior design/architecture and lifestyle. In order to maintain exclusivity the magazine cannot be purchased in a book store. It is circulated to a subscriber base of 40,000 readers, who are carefully selected depending on their income and social status to see if they fit the target audience of the magazine. As a result our subscriber base consists of 40,000 richest people in the country including celebrities, industrialist, top corporate etc. Because of this exclusivity and elite subscriber base high end luxury brands advertise with the magazine. All of these products are very expensive items which means their volume sales will be low but ticket size will be very large.</p>
<p></p>
<p><strong>Question</strong>: We have a database of these 40,000 richest people in the country including their name, address, gender, occupation, email etc. We want to leverage and monetize this data to do something that will add value to <strong>(i)</strong> the luxury brands who advertise with the magazine, <strong>(ii)</strong> the readers and <strong>(iii)</strong> brand value of the magazine. Could you please advice us on the various things that we can do with this data? We are open to all kinds of idea big or small so please feel free to share any suggestion.</p>
<p></p>
<p><strong>Here is a few sample suggestion:</strong></p>
<p>Create a monthly newsletter containing offers on luxury products and email them to the readers. This is what the advertisers want us to do because they want to reach out as much as possible to our readers. The flip side is we don't want to spam our readers with too many emails. But if we reduce the frequency of emails and give exclusive offers of big tickets items, our readers could be interested.</p>
<p></p>
<p>Regards,</p>
<p>Nilotpal</p> Burglary Forecasting for retail organizationtag:www.analyticbridge.com,2014-06-30:2004291:Topic:3000262014-06-30T09:36:39.265ZMatthew A. Riebelhttp://www.analyticbridge.com/profile/MatthewARiebel
<p>Hi,</p>
<p></p>
<p>Could anyone help me in creating of Burglary prediction model of retail stores at monthly level. This forecasting help to deploy appropriate resources at risky stores for mitigating the risk. The data I have:</p>
<p></p>
<p>1. Historical Burglary data at store level</p>
<p>2. Demographics data (static for one year)</p>
<p></p>
<p>We also considered some store specific variables but they all are also static, but I need a model that gives the monthly riskiness of each store…</p>
<p>Hi,</p>
<p></p>
<p>Could anyone help me in creating of Burglary prediction model of retail stores at monthly level. This forecasting help to deploy appropriate resources at risky stores for mitigating the risk. The data I have:</p>
<p></p>
<p>1. Historical Burglary data at store level</p>
<p>2. Demographics data (static for one year)</p>
<p></p>
<p>We also considered some store specific variables but they all are also static, but I need a model that gives the monthly riskiness of each store from burglary point of view.</p>
<p></p>
<p>Thanks in advance.</p>
<p></p>
<p>Thanks,</p>
<p>Atul</p>
<p></p>
<p></p>
<p> </p>