2022-01-01
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Mathematical view of Bias-Variance trade-off

6 mins read The bias-variance trade-off is an important concept in statistics and machine learning. This is used to get better performance out […]
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2021-12-26
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Walk-forward optimization for algorithmic trading strategies on cloud architecture

11 mins read Table of Contents: Introduction Terminology Walk-forward Optimization Design of walk-forwards The Architecture Configuring cloud machines using Ansible Docker Swarm Optimization […]
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2021-12-10
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Understanding Gaussian Process

79 mins read Gaussian Process is a machine learning technique. You can use it to do regression, classification, among many other things. Being […]
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2021-11-29
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Solving six problems with Bayesian statistics

8 mins read 1) The first one is a warm-up problem. Suppose there are two full bowls of cookies. Bowl #1 has 10 […]
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2021-11-23
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Bahdanau and Luong Attention Mechanisms explained

11 mins read Conventional encoder-decoder architectures for machine translation encoded every source sentence into a fixed-length vector, irrespective of its length, from which […]
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2021-11-21
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Difference between Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP)

4 mins read Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP), are both methods for estimating variable from probability distributions or graphical […]
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2021-11-20
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Understanding Expectation-Maximization (EM) algorithm with an example in Python

7 mins read Suppose we have some data sampled from two different groups, red and blue: Here, we can see which data point […]
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2021-11-15
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Machine Learning From Scratch Series: Naive Bayes and Gaussian Naive Bayes

16 mins read Introduction Naïve Bayes algorithm is a supervised classification algorithm based on the Bayes theorem with strong (Naïve) independence among features. In machine learning and data […]
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2021-11-09
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The BERT Model

17 mins read The year 2018 has been an inflection point for machine learning models handling text (or more accurately, Natural Language Processing […]
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2021-11-08
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Using BERT for Sentence Sentiment Classification

11 mins read Progress has been rapidly accelerating in machine learning models that process language over the last couple of years. This progress […]
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2021-11-08
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Seq2Seq models, Attention Mechanism, and Transformers Explained

29 mins read Sequence-to-sequence models are deep learning models that have achieved a lot of success in tasks like machine translation, text summarization, […]
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2021-11-04
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A guide on Gradient Boosting models

22 mins read An introduction to additive modeling Before we get into boosting, let’s look at an example of what mathematicians call additive modeling because […]
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2021-11-02
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ARCH and GARCH models for Time Series Prediction in Python

11 mins read A change in the variance or volatility over time can cause problems when modeling time series with classical methods like […]
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2021-11-02
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Finding and removing seasonality in Time-Series Data with Python

17 mins read Seasonality in Time Series Time series data may contain seasonal variation. Seasonal variation, or seasonality, are cycles that repeat regularly […]
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2021-11-01
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ARIMA and SARIMA for Real-World Time Series Forecasting in Python

15 mins read Time series and forecasting have been some of the key problems in statistics and Data Science. Data becomes a time […]
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2021-11-01
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A review of techniques for Time Series prediction

43 mins read Working with time series data? Here’s a guide for you. In this article, you will learn how to compare and […]
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2021-10-19
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Difference between Probability Density and Probability

5 mins read The probability density at x can be greater than one but then, how can it integrate to one? It’s a […]
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2021-10-19
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What is Conjugate Prior?

5 mins read What is Prior? Prior probability is the probability of an event before we see the data. In Bayesian Inference, the prior […]
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2021-10-17
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Important probability distributions for Data Science with Python code

33 mins read For a data scientist aspirant, Statistics is a must-learn thing. It can process complex and challenging problems in the real […]
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2021-10-08
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Importance Sampling in Reinforcement Learning

5 mins read Motivation Importance sampling plays a key role in sampling inferencing and reinforcement learning RL. In RL, importance sampling estimates the […]
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