added Movie-recommender

README.md

@@ -1,27 +1,57 @@
 # Data Science Portfolio - Guberan
-This Portfolio is a compilation of all the Data Science and Data Analysis projects I have done for academic, self-learning and hobby purposes. This portfolio also contains my skills. It is updated on the regular basis.
+
+      This Portfolio is a compilation of all the Data Science and Data Analysis projects I have done for academic, self-learning and hobby purposes. This portfolio also contains my skills. It is updated on the regular basis.
 
 - **Email**: [mgrguber@gmail.com](mgrguber@gmail.com)
 - **LinkedIn**: [linkedin/bit-guber](https://www.linkedin.com/in/bit-guber)
 
+## Competitions
+
+[<img align="left" width="100%" height="150" src="images/header.png">](https://www.kaggle.com/code/ryanholbrook/evaluate-student-summaries-efficiency-lb)
+
+### [ <center>28th place in CommonLit - Evaluate Student Summaries by NLP</center> ](https://www.kaggle.com/code/ryanholbrook/evaluate-student-summaries-efficiency-lb)
+
+&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;The goal of this competition is to assess the quality of summaries written by students in grades 3-12. Paticipation will build a model that evaluates how well a student represents the main idea and details of a source text, as well as the clarity, precision, and fluency of the language used in the summary.<br><br>
+
+#### I can find my solution [here](https://github.com/bit-guber/CESS-kaggle)
+
+#
+
+#
+
+#
 
 ## Projects
 
-<img align="left" width="250" height="150" src="Crunchyroll Web Scraping/images/output.png"> **[Crunchyroll Web Scraping and Basic Analysis ]( Crunchyroll%20Web%20Scraping/Basic_Analysis.ipynb )**
+[<img align="left" width="250" height="150" src="images/movie-recommender-demo-page.png">](https://github.com/bit-guber/Movie-Recommender-demo) **[<center> Movie Recommendation Application </center> ](https://github.com/bit-guber/Movie-Recommender-demo)**
+
+<center>
+In this project I make <mark>Recommended system</mark> for Movies based on user liked movie collection. It more efficient and Accuracy By using SVD algorithm that trained on MovieLens Dataset.<br>
+It live <a href = "https://bit-guber-movie-recommender.vercel.app/" target="_blank" rel="noopener noreferrer" style = "font-size:20px;font-weight: bold;">now</a> 
+</center>
 
-In this project I make data pipeline from crunchyroll websites scraped data, ETL process scripts and gather few insights of crunchyroll anime community
+#
 
 #
 
-<br />
+##
+
+[<img align="left" width="250" height="150" src="Crunchyroll Web Scraping/images/output.png">](Crunchyroll%20Web%20Scraping/Basic_Analysis.ipynb) **[<center> Crunchyroll Web Scraping and Basic Analysis </center> ](Crunchyroll%20Web%20Scraping/Basic_Analysis.ipynb)**
+
+<center>
+In this project I make data pipeline from crunchyroll websites scraped data, ETL process scripts and gather few insights of crunchyroll anime community</center>
+
+#
+
+<br>
 
 ## Micro Projects
+
 - ### Random Analysis
-    - Simple Analysis of Cardiovascular Diseases Risk Prediction Dataset that present on kaggle [notebook](https://www.kaggle.com/code/bitguber/basic-analysis-brfss-eda)
+  - Simple Analysis of Cardiovascular Diseases Risk Prediction Dataset that present on kaggle [notebook](https://www.kaggle.com/code/bitguber/basic-analysis-brfss-eda)
 
-
 ## Core Competencies
 
 - **Methodologies**: Machine Learning, Deep Learning, Time Series Analysis, Natural Language Processing, Statistics, Explainable AI, A/B Testing and Experimentation Design, Big Data Analytics
-- **Languages**: Python (Pandas, Numpy, Scikit-Learn, Scipy, Keras, SeaBorn, Matplotlib), SQL, C++, Rust
-- **Tools**: MySQL, PowerBI, Git, PySpark, Amazon Web Services (AWS), MS Excel
+- **Languages**: Python (Pandas, Numpy, Scikit-Learn, Scipy, Keras, SeaBorn, Matplotlib), SQL, C++, Rust, Javascript, HTML, CSS
+- **Tools**: MySQL, PowerBI, Git, PySpark, MS Excel, Nltk, Transformers models(such as bert, gpt2, deberta-v3, etc..)