Giannis Tolios’ Post

𝗔𝗻 𝗔𝘄𝗲𝘀𝗼𝗺𝗲 𝗕𝗼𝗼𝗸 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀! 🖥️📊 Practical Statistics for Data Scientists is a book covering important statistical concepts, such as exploratory data analysis, sampling distributions and hypothesis testing, with code examples in both Python and R. This awesome book achieves a great balance between theoretical concepts and practical examples, while being friendly to beginners who don't necessarily come from a quantitative background. You can check the links below for more information, and make sure to follow me for regular data science content! 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 - 𝟮𝗻𝗱 𝗘𝗱𝗶𝘁𝗶𝗼𝗻: https://lnkd.in/d2rptd8F 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #python #machinelearning #deeplearning #linkedin

𝗔𝗻 𝗔𝘄𝗲𝘀𝗼𝗺𝗲 𝗕𝗼𝗼𝗸 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀! 📊💡 Practical Statistics for Data Scientists is a book covering important statistical concepts, such as exploratory data analysis, sampling distributions and hypothesis testing, with code examples available in Python and R. This amazing book strikes a balance between theoretical concepts and practical examples, while also being friendly to beginners who don't have a quantitative background. You can check the links below for more information, and make sure to follow me for regular data science content! 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 - 𝟮𝗻𝗱 𝗘𝗱𝗶𝘁𝗶𝗼𝗻: https://lnkd.in/d2rptd8F 𝗖𝗵𝗲𝗰𝗸 𝗔𝗹𝗽𝗵𝗮𝗦𝗶𝗴𝗻𝗮𝗹 𝗳𝗼𝗿 𝗮 𝘀𝘂𝗺𝗺𝗮𝗿𝘆 𝗼𝗳 𝘁𝗵𝗲 𝘁𝗼𝗽 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗿𝗲𝗽𝗼𝘀 𝗮𝗻𝗱 𝗽𝗮𝗽𝗲𝗿𝘀: https://bit.ly/3Q8akG4 #datascience #python #machinelearning #deeplearning #linkedin

📣 Exciting news! I'm thrilled to share with you a comprehensive tutorial on Multiple Linear Regression. 📊🔬 In this blog post, we'll explore the power of this statistical modeling technique using Python and the Statsmodels library. 🐍 Gain a deep understanding of the mathematics behind it and learn how to interpret model predictions like a pro. 🔗 Read the full article here: [Multiple Linear Regression Explained](https://ift.tt/TJQycuZ) Whether you're a data scientist, analyst, or someone interested in data-driven decision-making, this tutorial will equip you with the skills to build and interpret robust regression models. 🚀 Don't miss this opportunity to enhance your data analysis skills and unlock the potential of Multiple Linear Regression. Start reading now! 💡 #DataScience #MachineLearning #Statsmodel #Python

🚀 Day 137: Explored t-Tests in my data science journey: 1. Single sample t-Test: Evaluating sample mean against a known value. 2. Single sample t-Test in Code: Applied Python for real-world analysis. 3. Independent 2-sample t-Test: Comparing means of two independent groups. 4. Independent 2-sample t-Test in Code: Utilized Python for efficient analysis. 5. Paired 2-sample t-Test (With Code): Examining differences between related groups. Adding powerful statistical tools to my toolkit! 💼 #DataScience #StatisticalAnalysis #TTests #PythonCoding#DataScience #DataScientist #MachineLearning #ArtificialIntelligence #DeepLearning #BigData #Analytics #Python #DataVisualization #Statistics #Coding #LearningJourney #CareerDevelopment #AI #Tech #DataAnalytics #DataMining #DataDriven #Algorithm #DataSkills #ContinuousLearning #ProfessionalGrowth #DataAnalysis #DataEngineering #DataPreprocessing #DataWrangling #DataInsights #PredictiveAnalytics #MachineLearningModels #DataStorytelling #DataQuality #DataManagement #FeatureEngineering #ModelEvaluation #DataCareer #TechCommunity 

🏡📈 House Price Prediction Project Completed! 📈🏡 Exciting news! I've just completed a House Price Prediction project, following an amazing YouTube tutorial by codebasics. 🎉 This tutorial helped me to understand the flow of the data science project and how machine learning models are deployed and how data is prepared for model building. Key Learnings: - Data Preprocessing: Data cleaning ✨ , Finding outliers , Dimensionality reduction  - Linear regression 📈 - K-fold cross validation - Insights & Visualization using Matplotlib 📈 Huge thanks to the tutorial creator for the guidance! 🙏 I'm eager to continue learning and applying my skills. 🌟 #DataScience #MachineLearning #housepriceprediction #pandas #numpy #python #matplotlib #linearregression #youtube

Here's another project I've worked on while learning machine learning! I built a Salary Prediction model based on years of experience. Using Python and Scikit-Learn, I implemented Linear Regression to develop a robust predictive model that estimates salaries with 89.14% accuracy. It's exciting to see how data science can help us make informed decisions.#DataScience #MachineLearning #SalaryPrediction.

📈 Empower Your Data-Driven Journey with Statistical Mastery! In Part 3 of our ongoing series on the basic principles of statistics, we delve into the core concepts that underpin sound data analysis:   🔹 Variance   🔹 Variances for Grouped Data 🔹 indispensable Standard Deviation These principles are the bedrock of informed decision-making, providing us with the tools to uncover patterns and insights in our data. 👉Are you ready to take your Statistical skills to the next level? 📌Join #1StepGrow and learn from industry experts who are paving the way to success.   🚀Follow 1stepGrow Academy for continuous learning and stay at the forefront of data science and machine learning excellence.  #1stepGrow_Academy #Statistics #DataScience #MacineLearning #python

Very important point in data science

A comprehensive brief on data analytics and insights, very useful for beginners who intend to capture and comprehend the concepts, rather than jumping into codes and modern tools like python. Subbing the fundamentals, usually complicates relating the business and practical needs to the vast application of todays modern analytical libraries and statistical tools. Converting a need into a practical, operational and data-oriented solution, often needs a mediator between the front line executers and technical developres, in which these basic concepts can be the common grounds for an effective and flawless communication. #analytics #distributions #dataanalysis #insights