SKU: 12882111707

Makita DGA 515 RF Akku Winkelschleifer 18 V 125 mm Brushless + 2x Akku 3,0 Ah + Ladegerät

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Description

Makita DGA 515 RF Akku Winkelschleifer 18 V 125 mm Brushless + 2x Akku 3,0 Ah + LadegerätLieferumfang: 1x Makita DGA 515 1x Makita Schruppscheibe INOX 125 mm 1x Seitengriff 1x Schutzhaube 2x Makita BL 1830 B 18 V 3,0 Ah Akku ( 197599 5 ) 1x Makita DC 18 RC Akku Ladegert 18 V ( 195584 2 ) Produktbeschreibung: Makita bietet hier mit dem DGA 515 einen leistungsstarken und kompakten Akku Winkelschleifer. Durch ADT ( Automatic torque Drive Technology ) wird die Drehzahl whrend des Betriebs automatisch reguliert und an die entsprechenden

Lieferumfang:

- 1x Makita DGA 515
- 1x Makita Schruppscheibe INOX 125 mm
- 1x Seitengriff 
- 1x Schutzhaube
- 2x Makita BL 1830 B 18 V 3,0 Ah Akku ( 197599-5 )
- 1x Makita DC 18 RC Akku Ladegerät 18 V ( 195584-2 )

Produktbeschreibung:

Makita bietet hier mit dem DGA 515 einen leistungsstarken und kompakten Akku Winkelschleifer. Durch ADT ( Automatic torque Drive Technology ) wird die Drehzahl während des Betriebs automatisch reguliert und an die entsprechenden Anforderungen angepasst. Die AFT ( Active Feedback sensing Technology) stoppt den Motor beim blockieren des Werkzeuges. Der DGA 515 verfügt über einen Sanftanlauf und eine elektronisch regelbare Drehzahl. Der verbaute bürstenlose ( Brushless ) Motor sorgt für eine kompaktere Bauweise, sowie einen niedrigeren Verschleiß und damit eine erhöhte Lebensdauer. Makita ist ein führender Hersteller für Elektrowerkzeug, der ich vor allem durch seine hohe Verarbeitungsqualität und sein riesiges 18 V Ökosystem auszeichnet.

Technische Daten:

Hersteller: Makita
Herstellerbezeichnung: DGA 515
Akkuspannung 18 V
Leerlaufdrehzahl: 3000 - 8500 min⁻¹
Max. Schnitttiefe: 29 mm
Bohrung: 22,23 mm
Max. Schleifscheiben-Ø: 125 mm
Gewicht inkl. Akku (EPTA): 2,4 - 3,1 kg
Produktabmessung (L x B x H): 382 x 140 x 151 mm
Schalldruckpegel (LpA): 79 dB(A)
K-Wert Geräusch: 3 dB(A)
Vibration: 5,5 m/s²
K-Wert Vibration: 1,5 m/s²


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SKU: 12882111707

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Zay
Whiting, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
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Reviewed in the United States on October 23, 2024
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Rory Derrick
Waukegan, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
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Cory P.
Lexington, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
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Frank Gonzalez
Birmingham, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
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Reviewed in the United States on April 7, 2024
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Ira Laefsky
Lake Worth, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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