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Why Momentum Really Works
Here’s a popular story about momentum [1, 2, 3] : gradient descent is a man walking down a hill. He follows the steepest path downwards; his progress is slow, but steady. Momentum is a heavy ball rol...
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Vibe Coding: A Hobby Today, the Future of Development Tomorrow?
Member-only story Vibe Coding: A Hobby Today, the Future of Development Tomorrow? Biljana Jelić Follow 7 min read · Just now -- Share Vibe coding has become my latest hobby, and I must admit, it’s pre...
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Exploring Deep Learning Models: Comparing ANN vs CNN for Image Recognition
Have you ever wondered how well Artificial Neural Networks (ANN) perform compared to Convolutional Neural Networks (CNN) in classifying… Continue reading on Towards AI
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Learn Python
▶️ Basic Functions
Syntax | Variables | Conditions |
Data Types | Numbers |
Strings | Formatting | Operators | Generators |
Decorators | Functions
| Lists | Tuples | Sets | Dictionaries | Parameters | Arguments |
Arrays | Linked Lists
| Hash Tables | Binary Search Trees | Recursion | Sorting
Algorithms | Exception Handling | Serialization
🚀 Advanced Functions
RegEx | Decorators | Lambdas | Iterators | Classes | Inheritance | Methods | List Comprehensions | Generator Expressions | PyPi | PIP | Conda
💠 Frameworks
Django | Flask | CherryPy | Bottle | Dash | | PyTest | Scrapy | PyScript |
🗂 Libraries
TensorFlow | Scikit-Learn | Numpy | Keras | PyTorch | SciPy | Pandas | Theano | Seaborn | OpenCV | Bokeh | Matplotlib | Plotly | BeautifulSoup | SymPy | Pillow
🧰 Other Tools
Selenium | PyCharm | PyTest | Jupyter Notebook | Faker | PyGame | Tkinter
Learn Data Science
▶️ Basics
Linear Algebra | Databases | Tabular Data | Time Series | Extract, Transform, Load | Data Formats | Regular Expressions | Important libraries |
💻 Programming languages for Data Science
SQL | R | Python
🐍 Python for Data Science
Syntax | Variables | Data Types | Functions | Numbers | Operators | Important libraries
🔁 Data Sources
Data Mining | Web scraping | Public Data Sets
📊 Exploratory Data Analysis
Principal Component Analysis | Dimensionality Reduction | Normalization | Data Cleaning | Estimators | Feature Extraction | Sampling
🔢 Statistics
Probability Theory | Continuous Distribution | Summary Statistics | Estimation | Hypothesis Testing | Confidence Interval | Monte Carlo Methods
📈 Data Visualization + tools
Storytelling | Charts | Dashboards | Power BI | Tableau | R | Dash | Seaborn | Matplotlib | Bokeh | Plotly
Learn Machine Learning
📊 Data
Labeling | Exploration | Preprocessing | Splitting | Augmentation
🧮 Modeling
Baselines | Evaluations | Experiment tracking | Optimization
♻️ Algorithms
Supervised Learning | Unsupervised Learning | Ensemble Learning | Reinforcement Learning | Linear Regression | Logistic Regression | Decision Tree | Random Forrest | Support Vector Machines | Naive Bayes | KNN Classification | K-Means
🔌 Use Cases
Computer Vision | Natural Language Processing | Recommender Systems | Pattern recognition
🗂 Frameworks & Libraries
Django | Flask | Keras | Numpy | Pandas | Scikit-Learn | Tensorflow | Matplotlib | PyTorch | Scipy | Hugging Face
🧰 Other tools
Docker | Kubernetes | MLflow
Learn Deep Learning
🧠 Neural Networks
Artificial Neural Networks | Convolutional Neural Networks | Recurrent Neural Networks | Transformers | Generative Adversarial Networks | Long Short Term Memory Networks
🧮 Training Methods
Optimizers | Learning Rate Schedule | Batch Normalization | Batch Size Effects | Regularization | Multi-task Learning | Transfer Learning
🗂 Frameworks & Libraries
Langchain | Django | Flask | Keras | Numpy | Pandas | Scikit-Learn | Tensorflow | Matplotlib | PyTorch | Scipy | Hugging Face
🧰 Other tools
Docker | Kubernetes | MLflow