Closer Consulting’s Post

"Excited to announce my completion of the DATA ANALYTICS certification! 🚀 Equipped with advanced skills in machine learning, I'm ready to tackle real-world data challenges and drive innovative solutions. Grateful for the learning journey with AICE and eager to apply my expertise in transforming businesses through AI. #Data Analytics #Certification #DataScience #AICE"

"Excited to announce my recent certification in Data Analytics and Machine Learning! 🚀📊 As the world becomes increasingly data-driven, I am equipped with the latest tools and techniques to uncover valuable insights and make data-powered decisions. Looking forward to applying my skills and contributing to innovative projects in the field of analytics and ML. #DataAnalytics #MachineLearning #CertifiedProfessional #DataDrivenDecisions"

🔍 Dive into Data Science with Tech Minds Education! 📊 Master the basics of machine learning and boost your career with our comprehensive course. Enroll now and start your data journey! 🚀📈  . . . 📞 Enroll Now : - 9650452738 🌐 www.techmindseducation.com . . . Follow for more @techmindseducation . . . #DataScience #MachineLearning #TechEducation #LearnDataScience #DataScienceCourse #AI #BigData #Analytics #DataAnalysis #TechMinds #DataScienceBasics #DataScienceTraining #TechSkills #FutureOfData #DataJourney

📊 Excited to share my latest resource on Data Science and Machine Learning! 🚀 Understanding key concepts is crucial for anyone diving into this field. I've created a comprehensive PDF that explains: *Dataset: The foundation of any data science project. *Supervised Learning: Learning from labeled data. *Unsupervised Learning: Finding hidden patterns in data. *Reinforcement Learning: Learning through trial and error. *Regularization: Techniques to prevent overfitting. *Data Wrangling: Preparing raw data for analysis. *Data Visualization: Transforming data into visual insights. *Outliers: Identifying anomalies in data. *Data Scaling: Adjusting data to a common scale. *Data Partitioning: Splitting data into training, validation, and test sets. Download the PDF to get a clear understanding of these essential terms and boost your knowledge in data science and machine learning. #DataScience #MachineLearning #AI #BigData #Analytics #SupervisedLearning #UnsupervisedLearning #ReinforcementLearning #Regularization #DataWrangling #DataVisualization #Outliers #DataScaling #DataPartitioning #TechEducation #ProfessionalDevelopment #LearningResources #CareerGrowth #DataAnalysis #TechSkills #Innovation #DataDriven

Very well structured,

Welcome to the seven days series of data analytics. #Day_1... #Today_is_the_kickoff_of_our_Data_Analytics_Series! 📊✨ We are thrilled to present the first video in this comprehensive journey into the world of data analytics. Whether you're looking to enhance your skills or start from scratch, this series is designed to provide valuable insights and practical knowledge. Check out the video and begin your path to becoming a data-driven professional. Let's unlock the power of data together! 🔗follow our page to be with us in this series...... #DataAnalytics #DataScience #BigData #MachineLearning #DataVisualization #Analytics #DataDriven #TechEducation #LearnData #TechCommunity #AI #BusinessIntelligence #Statistics #Coding #DataSkills #ProfessionalDevelopment #TechSeries #Innovation #FutureOfWork #CareerGrowth #TechLearning #DataProfessionals #ContinuousLearning

Handling Imbalanced Data with Under Sampling and Over Sampling 🚀 Hey Fellow Data Explorers! Continuing our ML journey, today, let's dive into the world of imbalanced data, where the key challenge is ensuring our models don't become biased, favoring "Yes" over "No". The "imblearn" library offers various techniques to tackle this problem and balance the data. Understanding Imbalanced Data: • Picture a scenario where 900 individuals love socializing ("Yes") while 100 prefer quiet evenings ("No"). • Training on this dataset might turn our model into an unwavering "Yes" supporter, introducing bias. Reducing Bias with Under Sampling and Over Sampling: 1. Under Sampling Approach: • Trimming the majority class to match the minority class's size. • Focuses on leveling by reducing the influence of the majority class. • Utilizes "NearMiss()" to strategically select samples from the majority class close to the minority class. • Keep in mind, it could potentially lose valuable information by removing data. 2. Over Sampling Approach: • Replicating or generating new instances of the minority class. • Boosts the representation of the minority class, promoting a more balanced dataset. • Leverages "SMOTETomek()" for synthetic instances and noise removal and "RandomOverSampler()" for strategic duplication. • There's a slight risk that it may lead to overfitting, especially if not approached with caution. Significance of the Strategy: • Precision in Model Performance: Balanced datasets ensure more accurate and unbiased model predictions. • Personalized approach : Choose your method wisely, whether it's under sampling or over sampling, based on your data's fine distinctions and the ML challenge at hand. In conclusion, our ML learning journey continues. Implement these techniques, experiment it wisely to understand deeper insights from your data.📚 Image Source : https://lnkd.in/d8Fiamt4 #machinelearning #dataanalysis #datapreprocessing #datapreparation #undersampling #oversampling #imblearn #datascience 🚀📈

😍 #ml #deeplearning "I am Fiaz Ul Hasan, a Data Scientist, and I have recently completed the course on 'Preparing Data for Machine Learning'. This comprehensive program equipped me with essential skills in data preprocessing, cleaning, and organizing, crucial for building robust machine learning models. I am excited to apply these techniques in real-world projects to drive impactful insights and solutions." 😍

Most Recommended Data Analytics Bootcamps in 2024 https://lnkd.in/gE5KgKaM Selecting the right bootcamp is crucial for your success. These top-notch bootcamps not only equip you with essential data analytics skills but also ensure a rewarding learning journey. Start your data analytics adventure today! #DataAnalyticsBootcamps #DataAnalyticsBootcampsin2024 #DataAnalytics #Bootcamps #DataAnalyticsTools #AI #AINews #AnalyticsInsight #AnalyticsInsightMagazine

Thrilled to share that I completed a transformative data analysis course a few months ago, and it was an incredible journey. The experience provided me with profound insights into the crucial role of data analysis in today's landscape. One of my key takeaways revolves around the significance of data cleaning and data visualization. In the realm of AI, where I'm currently immersed in my academic pursuits, the importance of meticulous data cleaning has become even more apparent. Ensuring the integrity of our data is paramount to obtaining accurate results from AI models. Moreover, the art of data visualization has proven to be a game-changer. Transforming numbers into insightful charts and graphs simplifies complex data sets, enabling a clearer understanding of the information at hand. This skill has proven invaluable in making sense of data and drawing meaningful conclusions. Here's to countless more discoveries and growth in the years ahead. #dataanalysis #ai #datascience #continuouslearning