Bahati Mulishi

Joined August 2024

32 stories

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Ways to Speed Up Your Python Code
10 Ways to Speed Up Your Python Code 1. List Comprehensions numbers = [x**2 for x in range(100000) if x % 2 == 0] instead of
By Bahati Mulishiabout a year ago in Geeks
Machine Learning Interview Question
ML Interview Question ⬇️ ➡️ Logistic Regression The interviewer asked to explain Logistic Regression along with its:
By Bahati Mulishiabout a year ago in Geeks
Java Roadmap
Java Roadmap Java Roadmap | |-- Fundamentals | |-- Basics of Programming | | |-- Introduction to Java | | |-- Java Development Kit (JDK) and Java Runtime Environment (JRE)
By Bahati Mulishiabout a year ago in Geeks
Typical C++ interview questions sorted by experience
Typical C++ interview questions sorted by experience Junior: - What are the key features of object-oriented programming in C++?
By Bahati Mulishiabout a year ago in Geeks
Introduction to Rust
Introduction to Rust What is Rust? Rust is a systems programming language designed for performance, reliability, and safety. It aims to provide memory safety without using a garbage collector, which makes it an excellent choice for system-level programming and performance-critical applications.
By Bahati Mulishiabout a year ago in Geeks
Data Science and Machine learning algorithms
For those of you who are new to Data Science and Machine learning algorithms, let me try to give you a brief overview. ML Algorithms can be categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.
By Bahati Mulishiabout a year ago in Geeks
Machine Learning
1. What is the AdaBoost Algorithm? AdaBoost also called Adaptive Boosting is a technique in Machine Learning used as an Ensemble Method. The most common algorithm used with AdaBoost is decision trees with one level that means with Decision trees with only 1 split. These trees are also called Decision Stumps. What this algorithm does is that it builds a model and gives equal weights to all the data points. It then assigns higher weights to points that are wrongly classified. Now all the points which have higher weights are given more importance in the next model. It will keep training models until and unless a lower error is received.
By Bahati Mulishiabout a year ago in Geeks
The Data Science skill no one talks about
The Data Science skill no one talks about... Every aspiring data scientist I talk to thinks their job starts when someone else gives them:
By Bahati Mulishiabout a year ago in Geeks
Concepts for Machine Learning
Key Concepts for Machine Learning Interviews 1. Supervised Learning: Understand the basics of supervised learning, where models are trained on labeled data. Key algorithms include Linear Regression, Logistic Regression, Support Vector Machines (SVMs), k-Nearest Neighbors (k-NN), Decision Trees, and Random Forests.
By Bahati Mulishiabout a year ago in Geeks
Advice on Machine Learning
95% of Machine Learning solutions in the real world are for tabular data. Not LLMs, not transformers, not agents, not fancy stuff.
By Bahati Mulishiabout a year ago in Geeks
data science concepts
Data Cleaning: Data cleaning is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in a dataset. It is a crucial step in the data science pipeline as it ensures the quality and reliability of the data.
By Bahati Mulishiabout a year ago in Geeks
Python in Data Science 📊
Essential Python Libraries to build your career in Data Science 1. NumPy: - Efficient numerical operations and array manipulation.
By Bahati Mulishiabout a year ago in Geeks