Pinned Repositories
Awesome-CV
:page_facing_up: Awesome CV is LaTeX template for your outstanding job application
BubMask__Bubble_detector
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
camcasp-bin
CamCASP binary repo
coding__cmake_fortran_template
A template directory structure for a Fortran project using CMake as the build system.
COVID-19_global_time_series_panel_data
Data-Analysis
Data Science Using Python
Ditching-Excel-for-Python
Functionalities in Excel translated to Python
DL-NLP-Readings
My Reading Lists of Deep Learning and Natural Language Processing
FortranPatterns
Popular design patterns implemented in Fortran.
psi4
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
ajmisquitta's Repositories
ajmisquitta/camcasp-bin
CamCASP binary repo
ajmisquitta/BubMask__Bubble_detector
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
ajmisquitta/GALAHAD_Optimization_library
A library of modern Fortran modules for nonlinear optimization
ajmisquitta/Intro-to-Machine-Learning-in-Chemistry
ajmisquitta/modern_fortran__csv-fortran
Read and Write CSV Files Using Modern Fortran
ajmisquitta/modern_fortran__neural-fortran
A parallel framework for deep learning
ajmisquitta/modern_fortran__tsunami
A parallel shallow water equations solver
ajmisquitta/modern_fortran__weather-buoys
Processing weather buoy data in parallel
ajmisquitta/python__data_analysis_and_visualisation__Rahul_Raoniar
Contains code and data for "The Researchers' Guide" Medium blogs
ajmisquitta/python__effective-pandas
Source code for my collection of articles on using pandas.
ajmisquitta/python__freecodecamp-intro-to-numpy
ajmisquitta/python__freecodecamp-intro-to-pandas
Python Pandas introduction.
ajmisquitta/python__FreeCodeCamp-Pandas-Real-Life-Example
ajmisquitta/python__freecodecamp_data-cleaning
Data cleaning
ajmisquitta/python__interactive-jupyterlab-tutorial
A quick tutorial on how to use Jupyter Lab (the evolution of Jupyter Notebooks).
ajmisquitta/python__milaan9__01_Python_Introduction
Learn the basics of Python. These tutorials are for Python beginners. so even if you have no prior knowledge of Python, you won’t face any difficulty understanding these tutorials.
ajmisquitta/python__milaan9__02_Python_Datatypes
Data types specify the different sizes and values that can be stored in the variable. For example, Python stores numbers, strings, and a list of values using different data types. Learn different types of Python data types along with their respective in-built functions and methods.
ajmisquitta/python__milaan9__03_Python_Flow_Control
Flow control is the order in which statements or blocks of code are executed at runtime based on a condition. Learn Conditional statements, Iterative statements, and Transfer statements
ajmisquitta/python__milaan9__04_Python_Functions
The function is a block of code defined with a name. We use functions whenever we need to perform the same task multiple times without writing the same code again. It can take arguments and returns the value.
ajmisquitta/python__milaan9__05_Python_Files
Python too supports file handling and allows users to handle files i.e., to read and write files, along with many other file handling options, to operate on files. The concept of file handling has stretched over various other languages, but the implementation is either complicated or lengthy, but like other concepts of Python, this concept here is
ajmisquitta/python__milaan9__06_Python_Object_Class
Object-oriented programming (OOP) is a method of structuring a program by bundling related properties and behaviors into individual objects. In this tutorial, you’ll learn the basics of object-oriented programming in Python.
ajmisquitta/python__milaan9__07_Python_Advanced_Topics
You'll learn about Iterators, Generators, Closure, Decorators, Property, and RegEx in detail with examples.
ajmisquitta/python__milaan9__09_Python_NumPy_Module
Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, Numpy can also be used as an efficient multi-dimensional container of generic data.
ajmisquitta/python__milaan9__10_Python_Pandas_Module
Pandas is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables.
ajmisquitta/python__milaan9__11_Python_Matplotlib_Module
Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. It was introduced by John Hunter in the year 2002. One of the greatest benefits of visualization is that it allows us visual access to hug
ajmisquitta/python__milaan9__12_Python_Seaborn_Module
Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk throug
ajmisquitta/python__pandas_exercises
Practice your pandas skills!
ajmisquitta/RALFit_NL_optimization_wt_Py
A non-linear least squares solver
ajmisquitta/SecondQuantization__Many-Body
Nuclear many-body course for 2018
ajmisquitta/spherical_tensors
Evaluate and transform D matrices, 3-j symbols, and (scalar or spin-weighted) spherical harmonics