Handling Missing Data and Categorical Features By: Bindeshwar Singh Kushwaha Data Preprocessing Flow Raw Data → Handle Missing Values → Encode Categorical Variables → Feature Scaling → Preprocessed Data Overview of Data Preprocessing Load Titanic dataset from CSV file Handle missing values using various techniques Encode categorical data for machine learning Save the cleaned dataset […]
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What is Data Preprocessing? Why It Matters in Machine Learning! Author: Bindeshwar Singh Kushwaha Real-World Data Challenges Missing or incomplete values Inconsistent formatting and typos Mixed data types (text, numeric, dates) Categorical variables needing encoding Scale variations and outliers What is Data Preprocessing? A set of techniques to clean and prepare raw data Essential for
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📘 Understand Poisson Distribution 📌 Introduction In binomial distributions, events’ occurrences and non-occurrences are equally important. However, in real-life situations: Events do not occur as outcomes of fixed number of trials. Events occur randomly over time. Interest lies only in the number of occurrences. Examples: Number of printing mistakes per page in a book. Number
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Binomial Distribution: Mean and Variance Problem 1: Mean = 3, Variance = 4? Given: Is it possible a binomial distribution has a mean of 3 and a variance of 4? Solution: Mean: \( \mu = np \) Variance: \( \sigma^2 = npq \), where \( q = 1 – p \) Given: \( np =
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Transfer Learning and Fine-Tuning Large Language Models In this post, we will explore the concept of Transfer Learning, its connection to fine-tuning large language models (LLMs), and step-by-step instructions to fine-tune DistilGPT-2. What is Transfer Learning? Transfer Learning is a powerful machine learning technique where a model trained on one task is reused as the
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Fitting Binomial Distribution Introduction Fitting a binomial distribution involves comparing observed frequencies with expected frequencies derived from the binomial probability formula. The recurrence relation simplifies the process of finding probabilities. This technique is useful for testing if a dataset follows a binomial distribution. Binomial Probability Function The binomial probability function is: $$p(x) = {n \choose
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Linear Dependence and Independence Definition Let \( V \) be a vector space over a field \( K \). Vectors \( v_1, v_2, \ldots, v_m \) in \( V \) are linearly dependent if there exist scalars \( a_1, a_2, \ldots, a_m \) in \( K \), not all zero, such that: \[ a_1 v_1
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Introduction to Robotics Simulation with PyBullet Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy What is Robotics? Robotics is an exciting and fast-growing interdisciplinary field that combines mechanical engineering, electrical engineering, computer science, and control systems. Robots are programmable machines capable of performing tasks automatically or semi-automatically, either with minimal human intervention or fully autonomously. The
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Span and Intersection of Subspaces Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Linear Span: Definition and Properties Given vectors \( u_1, u_2, \ldots, u_m \) in a vector space \( V \), their linear span is the set of all linear combinations: \[ \text{span}(u_1, u_2, \ldots, u_m) = \{ a_1 u_1 + a_2 u_2 +
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Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Sir Francis Galton: Biography and Contributions Quick Facts Name: Sir Francis Galton, FRS FRAI Born: 16 February 1822, Birmingham, England Died: 17 January 1911, Haslemere, Surrey, England (Aged 88) Resting Place: Claverdon, Warwickshire, England Education: King’s College London, Trinity College Cambridge Father: Samuel Tertius Galton Relatives: Charles