Pinned Repositories
Atomic-Algorithm-using-servers-to-find-Hamiltonian-Cycles
Atomic Algorithm-using servers to find Hamiltonian Cycles*, revisiting the concept, written by Mohamed Sghiar
Clustering
Cluster Set (Clustering + Set Theory), Holomorphic Encryption, K-Means, centroid-based algos, Image Data (by PCA), Big Data Clustering, Hierarchical, Two-Phase, DBScan
Dex-Hedge-in-Motoko
Decentralized Hedge-fund written in Motoko for the Internet Computer Protocol. (Using the help of ChatGPT)
Dex-Hedge-in-Solidity
Decentralized Hedge-fund converted from Motoko to Solidity (Testing of Translation techniques, Encoding/Compiling and language conversion) all possible routes exhausted
EtherPricePrediction
credit to: Namanjeet Singh, Kaggle , https://www.kaggle.com/code/namanjeetsingh/ethereum-cryptocurrency-prediction-using-rnn/notebook
MemorySystemsStudy
Approaching Python storage systems in the context of human-like ability, focus on AI
PricePrediction1stTry
BTC Price first, then try other coins
SciPy-and-ML-notes-LinReg-basics-
SkLearn's Imputer, Numpy and Panda's Imputer function (glazed over), imputation and extraction of null values, Ordinals, OneHot Encoders(OHE), Training/Testing data, LinReg
Seaborn-Practice
Simple-Python-PortScanner
deadSwank001's Repositories
deadSwank001/EtherPricePrediction
credit to: Namanjeet Singh, Kaggle , https://www.kaggle.com/code/namanjeetsingh/ethereum-cryptocurrency-prediction-using-rnn/notebook
deadSwank001/MemorySystemsStudy
Approaching Python storage systems in the context of human-like ability, focus on AI
deadSwank001/Simple-Python-PortScanner
deadSwank001/AppliedML-July
Mercedes-Benz Greener Manufacturing, Income Qualifications, DEL_SLR is salary and insurance,
deadSwank001/AppliedML-July2
Song Classification, Employer Turnover
deadSwank001/Clustering
Cluster Set (Clustering + Set Theory), Holomorphic Encryption, K-Means, centroid-based algos, Image Data (by PCA), Big Data Clustering, Hierarchical, Two-Phase, DBScan
deadSwank001/Data-in-Action
Part 2: Chapter 9) Contextualizing Problems and Data, The 5 Mistruths, Researching Solutions, Formulating a Hypothesis, Preparing Data, Feature Generation, Combining Variables, Understanding Binning and Discretization, Indicator Variables, Transforms, Array Operations, Vertices and Matrices
deadSwank001/Detecting-Outliers
Part 4: Chapter 16) anomalies and novel data, Gaussian distros, Assumptions, Multivariate Approach, PCA, Cluster Analysis for Outliers, Automating Detection with Isolation Forests
deadSwank001/EtherTrendAnalysis
credit to: Ayman Lafaz; Kaggle , https://www.kaggle.com/code/aymanlafaz/ethereum-trends-analysis/notebook
deadSwank001/EtherWithPython
Few price and sentiment analysis scripts in Python; that can be used on ANY stock or coin.
deadSwank001/Exploring-Data-Analysis
Iris Dataset, Kurtosis, Boxplots, Correlation, Chi-Test, Z-Score Distributions
deadSwank001/Four-Simple-and-Effective-algos
Linear Regression; family of linear models, adding variables, limitations, Logistic Regression, Naive Bayes, Predictive Text, KNN (K-Nearest Neighbors), predictions and k-parameters
deadSwank001/HashlibModule
All Python Encryption Services
deadSwank001/Increasing-Complexity
Chapter 19 Continued
deadSwank001/Langton-s_Ant_in_Bpy
Langton's Ant study in Python + Blender
deadSwank001/LinRegPractice2
Advertising dataset
deadSwank001/MatPlotLib-CrashCourse
deadSwank001/Performing-Cross-Validation-Selection-and-Optimization.py
How to fit a model, Understanding bias and variance, Strategy for picking models, Dividing Training/Testing, Cross-Validating, on K-Folds, Sampling stratification, Variable Selection, Greedy Search, Hyperparameters
deadSwank001/PuppetCase
Puppeteer; Docker, NodeJS, npm, no Debian/Alpine, Express Server build
deadSwank001/PythonPractice
Captain's log: day 249; all the Python modules I had skipped over from my original textbook, random.seed(), email, sms, FTP, news search, source clear, etc.
deadSwank001/Reducing-Dimensionality
SVD, Factor Analysis, Hidden Factors, Dimensionality Reduction, TSNE, Facial Rec with PCA, NMF, Random Forest Recommender
deadSwank001/Representing-SVM-Boundaries
Part 5: Chapter 19) Non-Linear and variable Transforms, Linear Models, L2 Ridge Regression, L1 Lasso, Regularization, L1 + L2: ElasticNet, Chunking Big Data, SGD, SVM> SVC, nonlinear w/ SVR, Stochastic SVM, Intro to NNs,
deadSwank001/Shaping-Data
Part 2: Chapter 8) Shaping Data, Parsing XML and HTML, Using XPath for data extraction, Working with Raw Text, Stemming and Removing stop words, Intro to Regex, BOW model, n-grams, TF-IDF transforms, Graph data (adjacency matrix, Networkx basics)
deadSwank001/Simplified-RAG-for-Video
Script using Ajax, Caffeine, for video database, takes LangChain input.
deadSwank001/Stretching-Pythons-Capabilities-Boston-Deprecated-Dataset-
Boston Real Estate Dataset deprecated for racial disparity [Multi-Threading practice]
deadSwank001/The-Power-of-Many
Decision Trees for different purposes, Accessible Machine Learning, Random Forest Classifier/Regressor; Optimizing, Boosting Predictions, GB Regressor, GBM Hyperparameters
deadSwank001/Translate-This
All translation libs in JavaScript. : Use Globalize, Polyglot
deadSwank001/ViolentlyDeterminedDuck_Backtest
QuantConnect_League starting Repo (RSI cross)
deadSwank001/Visualizing-Data
Pie Charts, Bar Charts, Showing Distributions using Histograms, Boxplots, Scatterplots, Correlations, Time Series, Geographical Data, Basemap Toolkit, Visualizing Graphs (undirected and directed)
deadSwank001/WhatShouldIDo-
MagicEightBall gone haywire