Sequence Model

The acronym SQL stands for Structured Query Language SQL is the standard language for data manipulation SQL is the standard language for relational database management. Three Main Uses of SQL are : Read ,Write , Update SQL is used for many things; however, Data Retrieval  was stressed as THE MAIN THING used by Data Scientist Data Scientist might do a little of the analysis using SQL, however the main thing they're using SQL for is data retrieval. Learning Objective: Explain why thinking before coding is important  Explain why it is important to understand how data in a database is relate to each other  Describe what a database is  Think before you do:    What is the problem you are trying to do..?     What I mean by this is it's easy when you're doing work or  we're trying to produce a result or solve a problem to just go in and start doing.  By that I mean you go in and start to write code or maybe start to write some  type of emai...

   M odel Evaluation Metrics Often, we think that precision and recall both indicate accuracy of the model. While that is somewhat true, there is a deeper, distinct meaning of each of these terms. Precision means the percentage of your results which are relevant. On the other hand,  recall refers to the percentage of total relevant results correctly classified by your algorithm . Undoubtedly, this is a hard concept to grasp in the first go. This is pretty intuitive. If you have to recall everything, you will have to keep generating results which are not accurate, hence lowering your precision. To exemplify this, imagine the case of digital world (again, amazon.com?), wherein there is a limited space on each webpage, and extremely limited attention span of the customer. Therefore, if the customer is shown a lot of irrelevant results and very few relevant results (in order to achieve a high recall), the customer will not keep browsing each and every product forever to final...

  Machine learning  is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.  basically Machine learning  focuses on the development of computer programs that can access data and use it learn for themselves. Currently,  machine learning  has been used in multiple fields and industries. For  example , medical diagnosis, image processing, prediction, classification,   regression etc Slide 2:  Machine Learning is categories in 3 parts  Supervised Learning  Unsupervised Learning Reinforecement Learning Slide 3: Supervised learning is where you have input variables (x) and an output variable (Y) and you use an algorithm to learn the mapping function from the input to the output. Y = f(X) The goal is to approximate the mapping function so well that when you have new input data (x) that you can predict the output variable...

Slide 0:   Machine Learning  Name Sourabh Agarwal  baki tere ko pata hi hai kya likhna hai  Slide-1  What is Machine Learning (ye haar page ke top pe likhna hai ) (jo jiss slide ka hai )(har pe topic likha hai slide ka )   Machine learning  is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed Currently,  machine learning  has been used in multiple fields and industries. For  example , medical diagnosis, image processing, prediction, classification,   regression etc Slide 2 Categories in machine Learning Supervised Learning  Unsupervised Learning Reinforecement Learning Slide 3 Supervised Learning Supervised learning is where you have input variables (x) and an output variable (Y) and you use an algorithm to learn the mapping function from the input to the output. Y = f(X) The goal is to approximate the...

  What is grid search? Grid search is the process of performing hyper parameter tuning in order to determine the optimal values for a given model.  This is significant as the performance of the entire model is based on the hyper parameter values specified. Why should I use it? If you work with ML, you know what a nightmare it is to stipulate values for hyper parameters. There are libraries that have been implemented, such as  GridSearchCV  of the  sklearn  library, in order to automate this process and make life a little bit easier for ML enthusiasts. How does it work? Here’s a python implementation of grid search using  GridSearchCV  of the  sklearn  library. How does it work? Here’s a python implementation of grid search using  GridSearchCV  of the  sklearn  library. from sklearn.model_selection import GridSearchCV from sklearn.svm import SVR gsc = GridSearchCV( estimator=SVR(kernel='rbf'), param_gri...