This Repository Consists of Free Resources needed for a person to learn Datascience from the beginning to end. This repository is divided into Four main Parts. They are: Part 1:- [Roadmap] Part 2:- [Free Online Courses] Part 3:- [500 Datascience Projects] Part 4:- [100+ Free Machine Learning Books] This repository is a combination of different resources lying scattered all over the internet. The reason for making such an repository is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Datascience.……

Statistics-101 for data noobs 1 Pick a dataset Datasets repositories Generalists KAGGLE Google Medical PMC Other languages French DATAGOUV 2 Descriptive statistics Mean In probability and statistics, population mean and expected value are used synonymously to refer to one _measure of the central tendency either of a probability distribution or of the random variable characterized by that distribution. For a data set, the terms arithmetic mean, mathematical expectation, and sometimes average are used synonymously to refer to a central value of a discrete set of numbers: specifically, the sum of the values divided by the number of values.……

Histograms are representation of distribution of numerical data. The procedure consists of binnng the numeric values using range divisions i.e, the entire range in which the data varies is split into several fixed intervals. Count or frequency of occurences of the numbers in the range of the bins are represented. Histograms In python, Pandas,Matplotlib,_Seaborn can be used to create Histograms. 5 Percentiles & outliers Percentiles Percentiles are numberical measures in statistics, which represents how much or what percentage of data falls below a given number or instance in a numerical data distribution.……

4 Machine learning 1 What is ML ? Definition Machine Learning is part of the Artificial Intelligences study. It concerns the conception, devloppement and implementation of sophisticated methods, allowing a machine to achieve really hard tasks, nearly impossible to solve with classic algorithms. Machine learning mostly consists of three algorithms: Utilisation examples Computer vision Search engines Financial analysis Documents classification Music generation Robotics … 2 Numerical var Variables which can take continous integer or real values.……

6 Data Visualization Open .R scripts in Rstudio for line-by-line execution. See 10 Toolbox/3 R, Rstudio, Rattle for installation. 1 Data exploration in R In mathematics, the graph of a function f is the collection of all ordered pairs (x, f(x)). If the function input x is a scalar, the graph is a two-dimensional graph, and for a continuous function is a curve. If the function input x is an ordered pair (x1, x2) of real numbers, the graph is the collection of all ordered triples (x1, x2, f(x1, x2)), and for a continuous function is a surface.……

Artificial Intelligence CS 188 - Introduction to Artificial Intelligence, UC Berkeley - Spring 2015 6.034 Artificial Intelligence, MIT OCW CS221: Artificial Intelligence: Principles and Techniques - Autumn 2019 - Stanford University 15-780 - Graduate Artificial Intelligence, Spring 14, CMU CSE 592 Applications of Artificial Intelligence, Winter 2003 - University of Washington CS322 - Introduction to Artificial Intelligence, Winter 2012-13 - UBC (YouTube) CS 4804: Introduction to Artificial Intelligence, Fall 2016 CS 5804: Introduction to Artificial Intelligence, Spring 2015 Artificial Intelligence - IIT Kharagpur Artificial Intelligence - IIT Madras Artificial Intelligence(Prof.……

500 AI Machine learning Deep learning Computer vision NLP Projects with code This list is continuously updated. - You can take pull request and contribute. Sr No Name Link 1 180 Machine learning Project is.gd/MLtyGk 2 12 Machine learning Object Detection is.gd/jZMP1A 3 20 NLP Project with Python is.gd/jcMvjB 4 10 Machine Learning Projects on Time Series Forecasting is.gd/dOR66m 5 20 Deep Learning Projects Solved and Explained with Python is.gd/8Cv5EP 6 20 Machine learning Project is.……

Summary The Conventional Commits specification is a lightweight convention on top of commit messages. It provides an easy set of rules for creating an explicit commit history; which makes it easier to write automated tools on top of. This convention dovetails with SemVer, by describing the features, fixes, and breaking changes made in commit messages. The commit message should be structured as follows: <type>[optional scope]: <description> [optional body] [optional footer(s)] The commit contains the following structural elements, to communicate intent to the consumers of your library:……

引言 Michael Simmons 的一篇「信息茧房自救指南」，非常适合当今信息过剩的情况下阅读，对于一个手机上没有抖音快手，没有新闻软件的人来说特别的棒。 “我们消费的……

A collection of recent methods on DNN compression and acceleration. There are mainly 5 kinds of methods for efficient DNNs: neural architecture re-design or search (NAS) maintain accuracy, less cost (e.g., #Params, #FLOPs, etc.): MobileNet, ShuffleNet etc. maintain cost, more accuracy: Inception, ResNeXt, Xception etc. pruning (including structured and unstructured) quantization matrix/low-rank decomposition knowledge distillation (KD) Note, this repo is more about pruning (with lottery ticket hypothesis or LTH as a sub-topic), KD, and quantization.……

常用符号的代码 1.上下标，正负无穷 数学表达式 LaTeX代码 $x^2$ x^2 $y_1$ y_1 $\infty$ \infty $-\infty$ -\infty 2.加减乘，分式，根号，省略号 数学表达式 LaTeX代码 $a+b-c*d$ a+b-c*d $a \div b$ a\div{b}……

零、开始 如果是对计算机一无所知或者不确定自己是否能走编程这条道路，那么我推荐你花 10 个小时看看《计算机科学速成课》，这套课程是 Crash Course 旗下的计算机……

前言 如今的笔记软件用户中，很多人会陷入「用笔记软件来记录如何使用笔记软件」的误区。即使避免了这个陷阱，也很可能花过不少功夫整理关于「卡片笔记……

Typora 一直是我认为桌面端笔记应用应有的终极形态。用我之前 一篇文章 中的话来说就是，「它的功能之强大、设计之冷静、体验之美妙、理念之先进，我认为值得……

业务部分 性能优化 建立完整，健康的性能优化管线。涉及程序，策划，美术，TA，PM，QA等多个职能组协作 使团队熟练掌握通用性能优化工具，设立角色……