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machine-learning_regression-project's Introduction

Hello, I'm Nishat Tasnim

I'm a curious explorer of the coding cosmos. While I may not wield languages like C, C++, Java, and Python with the mastery of a seasoned pro, I thrive on the thrill of creation and innovation. My digital palette includes dabbling in Machine Learning, spinning words into scientific gold, crafting visual wonders, and sculpting ideas into captivating PowerPoint presentations. Catch me occasionally cracking coding conundrums on Codechef and Codeforces, where challenges are my playground. But here's the twist: I'm not just about codes and algorithms. My heart beats for the enigmatic realm of research. Unveiling the mysteries of the universe, one data point at a time, gives me an electrifying high. Datasets are my playmates, and I believe that in every spreadsheet lies a story waiting to be told. Got a passion for the unconventional? Let's connect and embark on a journey of creativity, exploration, and mind-bending ideas. Together, let's transform the ordinary into the extraordinary! 🔍



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Coding

👩🏻‍💻 Who am I? (Breifly):

  • 🏫: I am a Student at Department of CSE at University of Asia Pacific.
  • 👩🏻‍🔬: I'm very passionate about Research, AI, HCI, ML, DL, NLP etc.
  • 💻: I love Graphics Design and writing Scientific Content, Sci-Fi.
  • 🧭: Always exploring and learning new things.

🔍 Find me elsewhere

codechef     Codeforces     hackerrank     Kaggle

stackoverflow     ResearchGate     TinkerCad

📩 Contact With Me:

Gmail     LinkedIn     Facebook

🛠️ My Skills

💻 Programming languages


python     java     C++     C Programming     SQL    


Click here for My Status...
{
   "Proficient": ["Python", "Java", "C", "C++", "SQL"],
   "Familiar with": ["HTML", "CSS"],
   "Database": ["MySql","MS SQL Server"],
   "AI framework":["Keras","Scikit-learn","PySpark","Tensorflow"],
   "Modules & Library":["Pandas","Numpy","Scipy","Matplotlib & seaborn","Folium & foursquare api","Beautifulsoup","Selenium","etc"],
                          
   "Machine Learning Algorithms": ["LinearRegression","LogisticRegression","KNeighborsRegressor","SVR","DecisionTree",
                                    "RandomForest","SVM","KNN","Naive Bayes","XGBoost", "AdaBoostClassifier","Lasso",
                                    "K-means","DBSCAN","Model Validation","Feature Selection","Dimensionality Reduction"],
   
   "Deep Learning": ["CNN","LSTM","Bi-LSTM","Transfer Learning","Model optimization and quantization",
                                    "TinyML","Pipelining","Keras sequential and functional API"]
}

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