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Quantifiers

Quantifiers is a complete guide where you can find articles on Machine Learning & Quantitative finance. We provide a complete roadmap to cracking Quantitative Finance Interviews/Strats Roles for Investment Banks and HFTs.

Hi, Welcome to Quantifiers. I am Priyanka Dalmia, currently pursuing MBA at IIM Bangalore. I have done my BE in Computer Science Engineering from BIT Mesra. I have worked as Software Engineer at Publicis Sapient. My interest lies in AI/ML, Finance and Product Management. 

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Model Drift in Machine Learning

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  We expect our model to perform the same as it does with the training data. However if the distribution of production data is different from that of the training data, this may lead to Model Drift. Model drift refers to the decay of the model’s predictive power. Model Drift occurs when: Training data is poorly sampled There is a change in the underlying business context Why is important to monitor Model Drift? It is necessary to monitor performance for model drift to ensure accurate predictions and check if retraining is required. Kinds of Drift Data Drift/Feature drift   — When there is a change in the input feature. Ta rget Drift   — When there is a change in the distribution of the target variable. Concept Drift   — When there is a change between the pattern or the relationship between the predictors and the outcome. Data Drift: This is also known as feature drift, population drift or covariate drift. Data drift is observed when there is a change in the distribut...
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Evolving ways of Data File Format

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  Data File Format define standard ways of storing information in a file or database. We require different file formats for different use cases. For example — If we know that only Python systems are going to read our file then we can choose Pickle format as it is highly optimized. CSV data format has been the most widely used opti o n for data storage. Using CSV, we can read from and write to most data software. However, there is no schema attached and no standard way to control characters and it is not the best way to deal with complex data. In this article, we will discuss the evolving ways of the data file format: Parquet:  Parquet is one of the most common data storage formats for Big Data as it is very fast. It also understands all the data types used by Pandas, including multi-index data frames. It is optimized to work with complex data in bulk and features different ways for efficient data compression and encoding types. It is mostly used as a data warehouse or data lak...
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Brain Teasers | Counterfeit Coins

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  Source: Google   Question:   I have10 bags with 100 identical coins in each bag. In all bags but one, each coin weighs 1 gram. However, all the coins in the counterfeit bag weigh either 0.9 or 1.1 grams. Can you help me find the counterfeit bag in only one weighing, using a digital scale that tells the exact weight?     Solution :     We will withdraw 1 coin from the 1 st  bag, 2 coins from the 2 nd  bag, 3 coins from the 3 rd  bag and so on...   Now we have Σ 1 + 2 + …+10 = 55 coins     If there are no counterfeit coins the sum total of weight should be 55 grams.   Let's assume that the  x th  bag  has counterfeit coins   Now the weight would come out to be 55 ± x     For example :     If bag 3 contains counterfeit coins and each of them weigh 1.1 grams   Then the  sum total of weight = 1 + 2 + 3*1.1 + 4 + 5 + 6 + 7 + 8 + 9 + 10 = 55.3   So ...
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