{"repo":"Hazrat-Ali9/Data-Scientist","free":true,"listed":false,"github":"https://github.com/Hazrat-Ali9/Data-Scientist","clone":"git clone https://github.com/Hazrat-Ali9/Data-Scientist.git","description":"🚂 Data 🚃 Scientist 🚋 is a curated 🚑 end to end 🚒 showcasing 🚞 real world ✈ data science 🚀 projects 🛸 machine 🚁 learning 🚟 models and ⛴ data 🛳 engineering 🛸 workflows 🚤 From data 🛼 wrangling to 🚒 deployment this 🚝 repo is proof ☂ of work and ⛱ personal 🛑 lab everything 🎳 data driven ⚽ Classification ⚾ regression 🥎 clustering NLP","language":null,"stars":42,"topics":["data","data-visualization","datascience-machinelearning","datascientist","python","scientific","scientists"],"license":null,"category":"machine-learning","readme_excerpt":"🤖 Hazrat Ali 🤡 Programmer Software Engineering 👻 Data Scientist Understand the Role of Data Scientist - Data Scientist ≈ Data Analysis Skills + Machine Learning & AI Knowledge 😊 Yes, It's True! What does a Data Scientist do? - Collect, clean, analyze, and interpret large datasets to provide actionable insights. - Build predictive models and machine learning algorithms. - Communicate results to stakeholders using visualizations and storytelling. - Collaborate with cross-functional teams to solve business problems using data. Responsibilities - Data collection, cleaning, and preparation. - Statistical analysis and predictive modeling. - Machine learning model development and evaluation. - Communicating insights through dashboards and visualizations. ----------------------------------------------- Step 1: Maths, Statistics and Probability Why Learn Math? - Builds problem-solving and analytical thinking skills. - Forms the foundation for ML algorithms, models, and data analysis. - Essential for understanding functions, optimization, and quantitative reasoning in data science and machine learning. Why Learn Statistics and Probability? - Understand data, patterns, and trends. - Essential for hypothesis testing, distributions, and inference. What to Learn? - Descriptive Statistics : Mean, median, mode, variance, standard deviation, percentiles. - Inferential Statistics : Hypothesis testing, confidence intervals, t-tests, z-tests, ANOVA. - Probability : Basics, conditional probab","default_branch":null,"files":null,"tree":[],"storefront":"/r/Hazrat-Ali9","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Hazrat-Ali9/Data-Scientist/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}