Day 12 of 365: .Today i learned how to code a linear regression model from scratch using python i learned two of the concept and after learning one i will be building a linear regression model from scratch for one parameter. #365DaysOfDataScience

RT @miniapeur:

Day 11 of 365:.Finally started to grasp the concept of Dimensionality Reduction and PCA 🎉.After many failed attempts, it’s finally clicking!.Huge shoutout to CampusX — the most GOATED 🐐 channel for breaking down tough concepts. #365DaysOfDataScience

Day 10 of 365:.Today I learned about K-Nearest Neighbors (KNN) 📍.➡️ Explored its meaning, applications, demerits, optimization techniques, and ideal use cases ⚙️📊.Planning to build some projects in the coming days! 💡💻.#365DaysOfDataScience #MachineLearning #KNN

Day 9 of 365:.Got hands-on with feature engineering today 🔧.✔️ Learned how to clean & prep data for modeling.✔️ Explored one-hot encoding and other preprocessing techniques.Now I know how to make raw data ML-ready! 💻📊.#100DaysOfDataScience #DataScience #FeatureEngineering

Day 9:.Learned how to build classifiers using Bayes’ Theorem → Naive Bayes Classifier 🤖.Also explored different types of data transformations for better model performance.Continued with normal distribution, dimensionality reduction, and linear algebra.#100DaysOfDataScience.

Day 8:.Dived into the world of statistics and math for data science today 📊.✔️ Learned about normal distribution.✔️ Explored dimensionality reduction techniques.✔️ Saw how linear algebra powers it all behind the scenes!.#365DaysOfDataScience #DataScience #MachineLearning

Day 7/365.🔍 Got hands-on with Exploratory Data Analysis (EDA) today.✅ Completed an exercise on DataCamp.📊 Analyzed the South Asia Happiness Index dataset from Kaggle.Enjoyed the data storytelling side of AI. #365DaysOfAI #EDA #DataAnalysis #Kaggle

Day 6/365.🧠 Learned how neural networks work under the hood with 3Blue1Brown — the math finally clicks!.📘 Also completed the Calculus for Deep Learning course. Feeling more confident with the math side of AI!.#365DaysOfAI

Day 5/365.Worked on my LangChain project:.🚀 Built a tool that ranks penny stocks based on multiple features and suggests if they're worth buying — on a scale of 0–40. Exciting to see AI + finance coming together! 💹🤖.#365DaysOfAI #LangChain #AIProjects #PennyStocks #FinTech

Day 4/100.✅ Finished the Matplotlib course on DataCamp.🚧 Started building a project using LangChain to automate quick market research on penny stocks and get actionable suggestions. Loving how everything’s starting to connect! 📊🤖.#100DaysOfAI #LangChain #Matplotlib #FinanceAI

Day 3/100.✅ Completed the LangChain course from Hugging Face.✅ Started learning Matplotlib on DataCamp.Now brainstorming project ideas to put LangChain into action. Excited to start building! 🚀.#100DaysOfAI #LangChain #Matplotlib #LLM #AIlearning

Day 2/365.Today I dove into LangChain — learned how it helps build efficient LLM apps, speeds up dev cycles, and makes chat-based features more dynamic. Super impressed with how much it can simplify the process!.I’m about 38% through the course and wrapped up a few lectures.

📊 Day 1 of Data Science Journey.Today I explored KDE (Kernel Density Estimation) — a powerful way to understand the general trend of data, even when it seems noisy. I practiced on a student performance dataset and realized how smooth curves can reveal hidden patterns 🔍

From today i want to get started with 365days of data science posting everything that i'll be learning and documenting everything i have learnt and taking feedback.

#LSPPDay60.Super happy that i have completed the 60 days challenge. Today, I learned about Big O notation and different types of time complexity, and which methods are best to use in programs to increase efficiency. #60DaysOfLearning2024 #LearningWithLeapfrog @lftechnology

#LSPPDay59. Today, I learned about time complexity, how to find the Big O notation (O(n)) of a program, and the methods to calculate it using programmiz. #60DaysOfLearning2024 #LearningWithLeapfrog @lftechnology

#LSPPDay58. Today, I learned about Bayes' theorem, which provides a mathematical rule for inverting conditional probabilities. Also learned how it can be used to invert the probability of observations given a model #60DaysOfLearning2024 #LearningWithLeapfrog @lftechnology

#LSPPDay57. Today, I learned about threading in Python and how to leverage it to speed up processing. Also covered the essential considerations to keep in mind while using threading. #60DaysOfLearning2024 #LearningWithLeapfrog @lftechnology

#LSPPDay56. Today, I learned how to use smtplib to send automatic emails and applied it to my automation project. Explored different methods to create emails using HTML text and attaching various files. #60DaysOfLearning2024 #LearningWithLeapfrog @lftechnology