emilstahl97
Studying Master's Programme, Software Engineering of Distributed Systems at KTH Royal institute of Technology.
Student at KTH Royal Institute of TechnologyStockholm, Sweden
Pinned Repositories
backblaze-docker
Building-Networked-Systems-Security-EP2520
This is a project based course that enhances and extends the understanding of modern networked systems security
Computer-Hardware-Engineering-IS1200
The course gives fundamental knowledge of computer organization, both from a hardware and software perspective.
Data-Intensive-Computing-ID2221
The course complements distributed systems courses, with a focus on processing, storing and analyzing massive data.
Distributed-Systems-ID2201
The course covers fundamental models for distributed systems, inter process communication and how to handle synchronization, consistency, replication, fault tolerance and security in a distributed system. The course consist of a series of lectures and seminars that include practical assignments.
Embedded-Electronics-IE1206
This course provides basic knowledge of circuit theory and electronics. It also provides knowledge of the various devices that can be found in a microcontroller and how these are supposed to be used.
Envariabelanalys-SF1625
Function, function graph, domain, range. Increasing and decreasing functions, odd and even functions. Inverse functions. The class of elementary functions. Trigonometric functions, exponential and logarithmic functions. Power laws, logarithms. Limits, rules for calculating limits, standard limits. Continuity, theorems on continuous functions. Derivative, rules of differentiation, the mean value theorem, implicit differentiation, applications: rate of change, linear approximation, tangent, extreme value problems, sketching the graph of a function, l'Hôpital's rule. Taylor's formula with error estimates. Linear differential equations with constant coefficients and their applications. The Riemann integral, primitive functions, the fundamental theorem integral calcolus, variable substitution, integration by parts, partial fractions. Riemann sums, geometric and other applications of integrals, improper integrals, estimates and convergence. Paramterization of curves and arc length. Sequences and series, convergence criteria, the Cauchy integral test. Taylor series.
Operating-Systems-ID1206
The course provides knowledge of the principles of and how one can implement abstractions of hardware virtualisation of resources and timetabling of assignments; mainly as regards execution, memory and persistent storage. The structure of an operating system is studied to increase the knowledge of these concepts and also give skills in efficient use of the abstraction level that an operating system offers.
Performance-analysis-of-the-FRRouting-Route-Server
Degree project researching the performance of FRRouting with a set of experiments using ExaBGP and Wireshark
Scalable-Machine-Learning-and-Deep-Learning-ID2223
The course studies fundamentals of distributed machine learning algorithms and the fundamentals of deep learning. We will cover the basics of machine learning and introduce techniques and systems that enable machine learning algorithms to be efficiently parallelized.
emilstahl97's Repositories
emilstahl97/Envariabelanalys-SF1625
Function, function graph, domain, range. Increasing and decreasing functions, odd and even functions. Inverse functions. The class of elementary functions. Trigonometric functions, exponential and logarithmic functions. Power laws, logarithms. Limits, rules for calculating limits, standard limits. Continuity, theorems on continuous functions. Derivative, rules of differentiation, the mean value theorem, implicit differentiation, applications: rate of change, linear approximation, tangent, extreme value problems, sketching the graph of a function, l'Hôpital's rule. Taylor's formula with error estimates. Linear differential equations with constant coefficients and their applications. The Riemann integral, primitive functions, the fundamental theorem integral calcolus, variable substitution, integration by parts, partial fractions. Riemann sums, geometric and other applications of integrals, improper integrals, estimates and convergence. Paramterization of curves and arc length. Sequences and series, convergence criteria, the Cauchy integral test. Taylor series.
emilstahl97/backblaze-docker
emilstahl97/Building-Networked-Systems-Security-EP2520
This is a project based course that enhances and extends the understanding of modern networked systems security
emilstahl97/Data-Intensive-Computing-ID2221
The course complements distributed systems courses, with a focus on processing, storing and analyzing massive data.
emilstahl97/emilstahl97
emilstahl97/Flervariabelanalys-KTH
emilstahl97/Linear-Algebra
Vectors, matrices, linear equations, Gaussian elimination, vector geometry with dot product and vector product, determinants, vector spaces, linear independence, bases, change of basis, linear transformations, the least-squares method, eigenvalues, eigenvectors, quadratic forms, orthogonality, inner-product space, Gram-Schmidt's method.
emilstahl97/Multivariable-Calculus-SF1626
Euclidian n-space. Functions of several variables and vector-valued functions, including the following concepts: Graph, level curve, level surface. Limits and continuity, differentiability, partial derivatives, the chain rule, differentials. Tangent planes and linear approximation. Taylor’s Formula. Gradient and directional derivative. Jacobian matrix and Jacobian determinant. Invertibility and implicitly defined functions. Coordinate changes. Extreme-value problems. Multiple integrals. Line integrals and Green’s theorem. Flux integrals and the divergence theorem. Stokes’ theorem. Applications.
emilstahl97/Networks-and-Communication-IK1203
The goals of the course is to teach the basics of networking and communication. For those interested in specializing in networking, it provides the fundamentals on which later courses build.
emilstahl97/Scalable-Machine-Learning-and-Deep-Learning-ID2223
The course studies fundamentals of distributed machine learning algorithms and the fundamentals of deep learning. We will cover the basics of machine learning and introduce techniques and systems that enable machine learning algorithms to be efficiently parallelized.
emilstahl97/Network-Programming--ID1212
Distributed applications that communicate over sockets. Distributed applications that communicate over RMI and message queues. Web applications and application servers. Framework, design and handling of threads for above-mentioned applications.
emilstahl97/Operating-Systems-ID1206
The course provides knowledge of the principles of and how one can implement abstractions of hardware virtualisation of resources and timetabling of assignments; mainly as regards execution, memory and persistent storage. The structure of an operating system is studied to increase the knowledge of these concepts and also give skills in efficient use of the abstraction level that an operating system offers.
emilstahl97/Performance-analysis-of-the-FRRouting-Route-Server
Degree project researching the performance of FRRouting with a set of experiments using ExaBGP and Wireshark
emilstahl97/alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
emilstahl97/Audio-dataset
emilstahl97/Concurrent-Programming-ID1217
The course covers the core concepts, models, paradigms and techniques for concurrent programming. This forms the basis for operating systems, distributed systems and multiprocessor systems, including multicore systems. The course studies foundations and principles of concurrent programming.
emilstahl97/Developing-Mobile-Applications-ID2216
The course is an introductory course in technologies to create mobile applications and mobile services. The course will teach the student’s efficient methods and practice on how to create native (Android) and platform independent (Web) mobile applications, as well as techniques for developing web-based mobile services.
emilstahl97/emilstahl97.github.io
emilstahl97/espeak-ng
eSpeak NG is an open source speech synthesizer that supports more than hundred languages and accents.
emilstahl97/gpt4all
gpt4all: a chatbot trained on a massive collection of clean assistant data including code, stories and dialogue
emilstahl97/gpt4free
decentralising the Ai Industry, free gpt-4/3.5 scripts through several reverse engineered api's ( poe.com, phind.com, chat.openai.com, phind.com, writesonic.com, sqlchat.ai, t3nsor.com, you.com etc...)
emilstahl97/guess-game
A school project regarding the HTTP protocol
emilstahl97/Hadoop-Hbase-Spark-Kafka
emilstahl97/Internetworking-IK1552
emilstahl97/Probability-Theory-and-Statistics-SF191X
emilstahl97/Programming-I-ID1018
Basic syntax and semantics of a higher-level language Variables, types, expressions and assignment Simple I/O Conditional and iterative control structures Functions and parameter passing Structured decomposition Data structures:
emilstahl97/Research-Methodology-and-Scientific-Writing-II2202
emilstahl97/screenshot-to-code
Drop in a screenshot and convert it to clean HTML/Tailwind/JS code
emilstahl97/stsbenchmark
emilstahl97/workload-generator
Workload Generator for Coflows